From 8fd4ebdf7111258acafe71cec7ce47ae0473bbf0 Mon Sep 17 00:00:00 2001 From: soneeee22000 <109932809+soneeee22000@users.noreply.github.com> Date: Mon, 1 Jun 2026 16:30:26 +0200 Subject: [PATCH] feat(experience): add Ekkhara founder role and SpeakProof project Lead the timeline with Ekkhara (Founder & Full-Stack / AI Engineer, self-employed, May 2026 - Present) building EdTech for Myanmar, and feature SpeakProof - a Telegram-native TOEFL practice bot that works without a VPN. Update About and hero to lead with the founder role since the Siloett contract has ended. - Add Ekkhara to EXP_META and SpeakProof (first featured) to PROJECTS_META - Hide the code button and add a 'live on Telegram' caption for demo-only projects - Renumber and translate experience + project copy across all 10 locales - Refresh SEO metadata and bump the projects stat to 12+ --- src/components/projects.tsx | 90 +++++++++++++++++--------------- src/lib/data.ts | 18 ++++++- src/messages/de.json | 96 ++++++++++++++++++---------------- src/messages/en.json | 100 +++++++++++++++++++----------------- src/messages/es.json | 96 ++++++++++++++++++---------------- src/messages/fr.json | 96 ++++++++++++++++++---------------- src/messages/ja.json | 96 ++++++++++++++++++---------------- src/messages/ko.json | 96 ++++++++++++++++++---------------- src/messages/my.json | 96 ++++++++++++++++++---------------- src/messages/pt.json | 96 ++++++++++++++++++---------------- src/messages/th.json | 96 ++++++++++++++++++---------------- src/messages/zh.json | 96 ++++++++++++++++++---------------- 12 files changed, 588 insertions(+), 484 deletions(-) diff --git a/src/components/projects.tsx b/src/components/projects.tsx index 98a1c38..b4ae35b 100644 --- a/src/components/projects.tsx +++ b/src/components/projects.tsx @@ -106,38 +106,42 @@ export function Projects() { {t("liveDemo")} ↗ )} - { - if (featured.demo !== "#") { - e.currentTarget.style.background = `${featured.color}12`; - } else { - e.currentTarget.style.opacity = "0.85"; - } - }} - onMouseLeave={(e) => { - if (featured.demo !== "#") { - e.currentTarget.style.background = "transparent"; - } else { - e.currentTarget.style.opacity = "1"; - } - }} - > - {featured.demo === "#" ? t("viewCode") : t("github")}{" "} - ↗ - + {featured.gh !== "#" && ( + { + if (featured.demo !== "#") { + e.currentTarget.style.background = `${featured.color}12`; + } else { + e.currentTarget.style.opacity = "0.85"; + } + }} + onMouseLeave={(e) => { + if (featured.demo !== "#") { + e.currentTarget.style.background = "transparent"; + } else { + e.currentTarget.style.opacity = "1"; + } + }} + > + {featured.demo === "#" ? t("viewCode") : t("github")}{" "} + ↗ + + )}
{featured.demo === "#" ? t("openSourceOnGithub") - : t("liveAtVercel")}{" "} + : featured.demo.includes("t.me") + ? t("liveAtTelegram") + : t("liveAtVercel")}{" "} ↗
@@ -204,14 +210,16 @@ export function Projects() { {t("demo")} ↗ )} - - {t("gh")} ↗ - + {p.gh !== "#" && ( + + {t("gh")} ↗ + + )}

diff --git a/src/lib/data.ts b/src/lib/data.ts index f65c5f6..0fcb178 100644 --- a/src/lib/data.ts +++ b/src/lib/data.ts @@ -20,6 +20,12 @@ export const GREETINGS: string[] = [ /** Experience metadata (non-translatable fields only) */ export const EXP_META = [ + { + company: "Ekkhara", + url: "https://ekkhara.com", + color: "#CC7B7B", + ptCount: 3, + }, { company: "Siloett.AI", url: "https://siloett.ai/lander", @@ -54,6 +60,16 @@ export const EXP_META = [ /** Project metadata (non-translatable fields only) */ export const PROJECTS_META = [ + { + id: 13, + featured: true, + emoji: "\uD83D\uDDE3\uFE0F", + title: "SpeakProof", + tags: ["Python", "Telegram Bot", "FastAPI", "LLM", "TOEFL"], + color: "#CC7B7B", + demo: "https://t.me/SpeakProofTOEFLBot", + gh: "#", + }, { id: 1, featured: true, @@ -437,7 +453,7 @@ export const SOCIAL_LINKS: [string, string][] = [ ["LINKEDIN", "https://www.linkedin.com/in/pyae-sone-kyaw-80386721b/"], ]; -export const STATS_NUMS = ["5+", "11+", "2", "3"]; +export const STATS_NUMS = ["5+", "12+", "2", "3"]; export const EDUCATION_META = [ { diff --git a/src/messages/de.json b/src/messages/de.json index b71f267..c39dc0a 100644 --- a/src/messages/de.json +++ b/src/messages/de.json @@ -14,7 +14,7 @@ "resume": "LEBENSLAUF" }, "hero": { - "subtitle": "FULL-STACK AI ENGINEER · STATION F · PARIS", + "subtitle": "GRÜNDER · FULL-STACK- & KI-INGENIEUR · PARIS", "specialties": "AI Engineering · Full-Stack Systems · Backend & Cloud Data", "openTo": "OPEN TO AI / FULL-STACK / BACKEND ROLES · FR / DE / UK", "viewWork": "ARBEITEN ANSEHEN", @@ -26,7 +26,7 @@ "heading": "AI Engineer · Full-Stack ·", "headingEm": "Backend Systems", "quote": "AI Engineer · Full-Stack · Backend Systems — building production-grade software at the intersection of telecom, healthcare, and finance, across Asia and Europe.", - "p1": "Currently a Full-Stack AI Engineer at Siloett.AI (Station F, Paris), where I architect end-to-end Generative AI systems on Azure with FastAPI, Azure Functions, and React/TypeScript.", + "p1": "Derzeit Gründer von Ekkhara, einem eigenfinanzierten Software- & KI-Studio, das EdTech für Myanmar entwickelt — zuletzt SpeakProof, ein Telegram-nativer TOEFL-Übungsbot, der ohne VPN funktioniert. Zuvor Full-Stack-KI-Ingenieur bei Siloett.AI (Station F, Paris), wo ich durchgängige generative KI-Systeme auf Azure mit FastAPI und React/TypeScript entwarf.", "p2": "Beyond AI, my engineering portfolio spans backend systems — Java 21, Spring Boot 3.5, Kafka, microservices — and cloud data engineering on AWS, Snowflake, Databricks, dbt, and Airflow. Telecom domain depth includes CDR pipelines, SMPP gateways, and Diameter Credit-Control.", "p3": "Dual Master's degrees from Telecom SudParis (Paris) and AIT (Bangkok), plus 5+ years shipping production software across healthcare, RegTech, telecom, and smart-city domains.", "p4": "Currently exploring AI Engineer, Full-Stack, and Backend Engineer roles across France, Germany, and the UK. If you're hiring or know of a fit — let's talk.", @@ -40,37 +40,43 @@ "label": "02 — EXPERIENCE", "heading": "Wo ich", "headingEm": "gebaut & gelernt habe", - "0_job": "Full-Stack AI Engineer", - "0_badge": "AI Safety & Compliance · Station F · Paris", - "0_date": "Jun 2025 — May 2026", - "0_pt0": "Architektur und Aufbau einer End-to-End Generative-AI-Plattform von Grund auf — LLM-Orchestrierung, RAG-Pipelines und ein produktionsreifes React/TypeScript-Frontend mit Python (FastAPI) und Azure Functions Serverless-Backend", - "0_pt1": "Entwurf und Implementierung verantwortungsvoller AI-Validierungsschichten einschließlich Content-Safety-Filter, Bias-Erkennungsprüfungen und Compliance-Leitplanken, die sicherstellen, dass alle AI-generierten Ausgaben regulatorische und ethische Standards erfüllen", - "0_pt2": "Aufbau von AI-Sicherheits- und IP-Compliance-Systemen einschließlich Audit-Logging, Herkunftsverfolgung und Output-Attributions-Pipelines — für nachvollziehbare und verantwortliche AI-Output-Lebenszyklen", - "0_pt3": "Entwicklung von Prompt-Engineering- und LLM-Evaluierungs-Frameworks mit Azure OpenAI GPT-4o und LangChain, mit systematischem Fine-Tuning zur Optimierung der Domänengenauigkeit über Compliance-Anwendungsfälle", - "1_job": "Data Science / Cloud Data Engineer", - "1_badge": "Station F · Paris", - "1_date": "Jul 2024 — Dec 2025", - "1_pt0": "Entwurf einer cloudbasierten Batch-Datenverarbeitungspipeline mit Microsoft Azure Batch und Docker für urbane Mobilitätsanalytik", - "1_pt1": "Automatisierung von Computer-Vision- und Bluetooth-Sensor-Workflows für skalierbare Echtzeit-Smart-City-Einblicke", - "1_pt2": "Bereitstellung von Produktionsanalyse-Dashboards, die von Stadtverwaltungen und Verkehrsverantwortlichen übernommen wurden", - "2_job": "Research & Back-End Engineer", - "2_badge": "Computer Vision · Backend-KI", - "2_date": "Aug 2023 — Jul 2024", - "2_pt0": "Back-End-Services und Datenpipelines für ein Forschungslabor entwickelt, das angewandte KI-Fähigkeiten für Partnerorganisationen bereitstellt — Computer-Vision- und NLP-Forschung über Python-APIs in Produktion gebracht", - "2_pt1": "Ein vollständiges Englisch–Myanmar-Maschinenübersetzungssystem auf einem manuell kuratierten WikiHow-Korpus mit 10K Beispielen aufgebaut — von Datensatzerstellung über Training und Evaluierung bis zum Deployment hinter einer öffentlichen API", - "2_pt2": "Neuartige Forschungsprototypen in Computer Vision und mehrsprachigem NLP sowie die Back-End-Infrastruktur dafür entwickelt — Laborforschung in reproduzierbare, einsatzfähige Tools überführt", + "0_job": "Gründer & Full-Stack- / KI-Ingenieur", + "0_badge": "Gründer · EdTech für Myanmar", + "0_date": "May 2026 — Present", + "0_pt0": "Gründung von Ekkhara, einem eigenfinanzierten Software- & KI-Studio, das EdTech-Produkte für Myanmar entwickelt — jedes Produkt von der Idee bis zum Live-Gang, mit voller Verantwortung für Architektur, Backend, KI und Frontend.", + "0_pt1": "Entwicklung von SpeakProof, einem TOEFL-Speaking- und Englisch-Übungsbot, der vollständig in Telegram läuft — so können Lernende in Myanmar aus einer täglich genutzten App für den TOEFL-Computertest üben, ganz ohne VPN trotz der Internet-Beschränkungen des Landes.", + "0_pt2": "Entwicklung der gesamten Stack hinter jedem Produkt — Python-/FastAPI-Services, LLM-gestütztes Feedback und Scoring sowie konversationelle UX — und Auslieferung von KI-Tools, die Nutzer auch dort erreichen, wo Zugang und Infrastruktur begrenzt sind.", + "1_job": "Full-Stack AI Engineer", + "1_badge": "AI Safety & Compliance · Station F · Paris", + "1_date": "Jun 2025 — May 2026", + "1_pt0": "Architektur und Aufbau einer End-to-End Generative-AI-Plattform von Grund auf — LLM-Orchestrierung, RAG-Pipelines und ein produktionsreifes React/TypeScript-Frontend mit Python (FastAPI) und Azure Functions Serverless-Backend", + "1_pt1": "Entwurf und Implementierung verantwortungsvoller AI-Validierungsschichten einschließlich Content-Safety-Filter, Bias-Erkennungsprüfungen und Compliance-Leitplanken, die sicherstellen, dass alle AI-generierten Ausgaben regulatorische und ethische Standards erfüllen", + "1_pt2": "Aufbau von AI-Sicherheits- und IP-Compliance-Systemen einschließlich Audit-Logging, Herkunftsverfolgung und Output-Attributions-Pipelines — für nachvollziehbare und verantwortliche AI-Output-Lebenszyklen", + "1_pt3": "Entwicklung von Prompt-Engineering- und LLM-Evaluierungs-Frameworks mit Azure OpenAI GPT-4o und LangChain, mit systematischem Fine-Tuning zur Optimierung der Domänengenauigkeit über Compliance-Anwendungsfälle", + "2_job": "Data Science / Cloud Data Engineer", + "2_badge": "Station F · Paris", + "2_date": "Jul 2024 — Dec 2025", + "2_pt0": "Entwurf einer cloudbasierten Batch-Datenverarbeitungspipeline mit Microsoft Azure Batch und Docker für urbane Mobilitätsanalytik", + "2_pt1": "Automatisierung von Computer-Vision- und Bluetooth-Sensor-Workflows für skalierbare Echtzeit-Smart-City-Einblicke", + "2_pt2": "Bereitstellung von Produktionsanalyse-Dashboards, die von Stadtverwaltungen und Verkehrsverantwortlichen übernommen wurden", "3_job": "Research & Back-End Engineer", - "3_badge": "Angewandte-KI-Labor · Backend", - "3_date": "Jan 2023 — Aug 2023", - "3_pt0": "Ein NLP-Paraphrasierungstool durchgängig in einem Forschungslabor entwickelt, das angewandte KI-Dienste für Unternehmen anbietet — vom Modell bis zur Back-End-API", - "3_pt1": "Die Datenschicht aufgebaut — Bereinigung und Strukturierung von Trainingsdatensätzen — und Trainings-Workflows optimiert, wodurch die Modellgenauigkeit um 15 % verbessert wurde", - "3_pt2": "Verantwortlich für den Back-End-Betrieb der KI-Tools des Labors, mit Stärkung von Datenmanagement und R&D-Engineering-Praxis", - "4_job": "Software Engineer (Web)", - "4_badge": "Full-Stack Web · UN-Organisation", - "4_date": "Jan 2021 — Dec 2022", - "4_pt0": "Full-Stack-Webanwendungen für eine UN-Organisation (FAO) entwickelt — interne Daten-Dashboards und öffentliche Portale, die Programmdaten zu Landwirtschaft und Ernährungssicherheit für Mitarbeitende und Außenteams bereitstellen", - "4_pt1": "Tools zur Felddatenerfassung und die zugehörigen Back-End-APIs entwickelt, mit denen Außendienstmitarbeitende Programmdaten erfassen, validieren und in zentrale Reporting-Systeme synchronisieren konnten", - "4_pt2": "Features end-to-end über den gesamten Stack verantwortet — React/Next.js + TypeScript Front-Ends mit Python- und PHP/CMS-Back-Ends — vom Datenmodell und REST API bis zur deployten UI" + "3_badge": "Computer Vision · Backend-KI", + "3_date": "Aug 2023 — Jul 2024", + "3_pt0": "Back-End-Services und Datenpipelines für ein Forschungslabor entwickelt, das angewandte KI-Fähigkeiten für Partnerorganisationen bereitstellt — Computer-Vision- und NLP-Forschung über Python-APIs in Produktion gebracht", + "3_pt1": "Ein vollständiges Englisch–Myanmar-Maschinenübersetzungssystem auf einem manuell kuratierten WikiHow-Korpus mit 10K Beispielen aufgebaut — von Datensatzerstellung über Training und Evaluierung bis zum Deployment hinter einer öffentlichen API", + "3_pt2": "Neuartige Forschungsprototypen in Computer Vision und mehrsprachigem NLP sowie die Back-End-Infrastruktur dafür entwickelt — Laborforschung in reproduzierbare, einsatzfähige Tools überführt", + "4_job": "Research & Back-End Engineer", + "4_badge": "Angewandte-KI-Labor · Backend", + "4_date": "Jan 2023 — Aug 2023", + "4_pt0": "Ein NLP-Paraphrasierungstool durchgängig in einem Forschungslabor entwickelt, das angewandte KI-Dienste für Unternehmen anbietet — vom Modell bis zur Back-End-API", + "4_pt1": "Die Datenschicht aufgebaut — Bereinigung und Strukturierung von Trainingsdatensätzen — und Trainings-Workflows optimiert, wodurch die Modellgenauigkeit um 15 % verbessert wurde", + "4_pt2": "Verantwortlich für den Back-End-Betrieb der KI-Tools des Labors, mit Stärkung von Datenmanagement und R&D-Engineering-Praxis", + "5_job": "Software Engineer (Web)", + "5_badge": "Full-Stack Web · UN-Organisation", + "5_date": "Jan 2021 — Dec 2022", + "5_pt0": "Full-Stack-Webanwendungen für eine UN-Organisation (FAO) entwickelt — interne Daten-Dashboards und öffentliche Portale, die Programmdaten zu Landwirtschaft und Ernährungssicherheit für Mitarbeitende und Außenteams bereitstellen", + "5_pt1": "Tools zur Felddatenerfassung und die zugehörigen Back-End-APIs entwickelt, mit denen Außendienstmitarbeitende Programmdaten erfassen, validieren und in zentrale Reporting-Systeme synchronisieren konnten", + "5_pt2": "Features end-to-end über den gesamten Stack verantwortet — React/Next.js + TypeScript Front-Ends mit Python- und PHP/CMS-Back-Ends — vom Datenmodell und REST API bis zur deployten UI" }, "projects": { "label": "03 — PROJECTS", @@ -83,19 +89,21 @@ "demo": "DEMO", "gh": "GH", "liveAtVercel": "LIVE ON VERCEL", + "liveAtTelegram": "LIVE ON TELEGRAM", "openSourceOnGithub": "OPEN-SOURCE ON GITHUB", - "0_desc": "Real-time European grid lakehouse on AWS — probabilistic load forecasting (DeepAR / quantile loss) and stochastic optimisation for battery flexibility decisions. Medallion architecture on S3 + Iceberg, MSK Kafka streaming, dbt models, Airflow orchestration, MLflow tracking. Cloud Data Engineering portfolio piece.", - "1_desc": "Event-driven Call Detail Record ingestion, rating, and reconciliation pipeline simulating an MVNO billing back-end. Idempotent Kafka consumers, Spring Boot 3.5 microservices, MySQL for rated CDRs, MongoDB for raw events, Docker Compose for local infra. Built around real telecom domain models (3GPP TS 32.298).", - "2_desc": "End-to-end CSRD/ESRS sustainability data pipeline — Claude/Mistral GenAI extraction from sustainability reports with page-level audit lineage, Snowflake warehouse (validated) + DuckDB local dev, dbt transformations, Airflow orchestration. Built for EU corporate sustainability reporting compliance.", - "3_desc": "AI-powered blood test interpretation for personalised supplement guidance — competing at Haleon VivaTech 2026. OCR ingestion of French lab reports, validated biomarker classification, longitudinal tracking, and supplement recommendations grounded in clinical evidence. Real-data moat through partner lab integrations.", - "4_desc": "From-scratch ReAct Agent Observatory — observe, debug, and benchmark LLM agents with a built-in 8-type failure taxonomy (hallucinated tools, malformed actions, context overflow, goal drift, …) and multi-provider eval harness (Groq, OpenAI, Anthropic, Google, Ollama). Composite scoring (answer + tools + efficiency + reliability), Clean Architecture FastAPI + PostgreSQL backend, Next.js 16 frontend with real-time SSE streaming. 50+ benchmark cases, 81 tests.", - "5_desc": "Real-World Evidence platform for vaccine research — full-stack application for ingesting, analyzing, and visualizing vaccine safety and efficacy data from real-world sources at scale. Built at Siloett.AI for healthcare and life-sciences buyers.", - "6_desc": "Diameter Credit-Control Server (Gy / RFC 4006 / App-Id 4) for real-time prepaid mobile billing. Idempotent partial debits, jdiameter 1.7.x stack, designed against TRANSATEL/MVNO production patterns.", - "7_desc": "Java SMPP v3.4 gateway bridging inbound SMS (submit_sm) to RabbitMQ for downstream processing. Spring Boot 3.5 + jsmpp 3.0, dockerised, designed for MVNO and telecom messaging platforms.", - "8_desc": "Real-time urban mobility analytics on TimescaleDB + PostGIS + Uber H3. Spring Boot ingestion, Kafka stream processing, Server-Sent Events for live dashboards. Smart-city back-end blueprint.", - "9_desc": "Reference implementation of the BCBS 239 risk-data-aggregation lakehouse pattern on Databricks + Delta Lake + Unity Catalog + dbt-databricks. MIT-licensed, synthetic data only — banking risk-data engineering portfolio piece.", - "10_desc": "Serverless middleware enforcing responsible-AI compliance on LLM applications — PII detection, bias screening, hate-speech filtering, and RAG-powered policy enforcement on top of Azure OpenAI.", - "11_desc": "Cloud Carbon Intelligence platform estimating CO2e emissions from Azure infrastructure with AI-powered reduction recommendations. Clean Architecture, Azure AI Search semantic factor lookup, 88 automated tests. Built for EU CSRD Scope 3 compliance." + "0_desc": "Telegram-native TOEFL speaking & English-practice bot for Myanmar learners — drill toward the TOEFL computer-based test inside an app people already use daily, with zero VPN needed despite nationwide internet restrictions. LLM-powered speaking feedback and scoring on a Python / FastAPI backend. An Ekkhara EdTech product.", + "1_desc": "Real-time European grid lakehouse on AWS — probabilistic load forecasting (DeepAR / quantile loss) and stochastic optimisation for battery flexibility decisions. Medallion architecture on S3 + Iceberg, MSK Kafka streaming, dbt models, Airflow orchestration, MLflow tracking. Cloud Data Engineering portfolio piece.", + "2_desc": "Event-driven Call Detail Record ingestion, rating, and reconciliation pipeline simulating an MVNO billing back-end. Idempotent Kafka consumers, Spring Boot 3.5 microservices, MySQL for rated CDRs, MongoDB for raw events, Docker Compose for local infra. Built around real telecom domain models (3GPP TS 32.298).", + "3_desc": "End-to-end CSRD/ESRS sustainability data pipeline — Claude/Mistral GenAI extraction from sustainability reports with page-level audit lineage, Snowflake warehouse (validated) + DuckDB local dev, dbt transformations, Airflow orchestration. Built for EU corporate sustainability reporting compliance.", + "4_desc": "AI-powered blood test interpretation for personalised supplement guidance — competing at Haleon VivaTech 2026. OCR ingestion of French lab reports, validated biomarker classification, longitudinal tracking, and supplement recommendations grounded in clinical evidence. Real-data moat through partner lab integrations.", + "5_desc": "From-scratch ReAct Agent Observatory — observe, debug, and benchmark LLM agents with a built-in 8-type failure taxonomy (hallucinated tools, malformed actions, context overflow, goal drift, …) and multi-provider eval harness (Groq, OpenAI, Anthropic, Google, Ollama). Composite scoring (answer + tools + efficiency + reliability), Clean Architecture FastAPI + PostgreSQL backend, Next.js 16 frontend with real-time SSE streaming. 50+ benchmark cases, 81 tests.", + "6_desc": "Real-World Evidence platform for vaccine research — full-stack application for ingesting, analyzing, and visualizing vaccine safety and efficacy data from real-world sources at scale. Built at Siloett.AI for healthcare and life-sciences buyers.", + "7_desc": "Diameter Credit-Control Server (Gy / RFC 4006 / App-Id 4) for real-time prepaid mobile billing. Idempotent partial debits, jdiameter 1.7.x stack, designed against TRANSATEL/MVNO production patterns.", + "8_desc": "Java SMPP v3.4 gateway bridging inbound SMS (submit_sm) to RabbitMQ for downstream processing. Spring Boot 3.5 + jsmpp 3.0, dockerised, designed for MVNO and telecom messaging platforms.", + "9_desc": "Real-time urban mobility analytics on TimescaleDB + PostGIS + Uber H3. Spring Boot ingestion, Kafka stream processing, Server-Sent Events for live dashboards. Smart-city back-end blueprint.", + "10_desc": "Reference implementation of the BCBS 239 risk-data-aggregation lakehouse pattern on Databricks + Delta Lake + Unity Catalog + dbt-databricks. MIT-licensed, synthetic data only — banking risk-data engineering portfolio piece.", + "11_desc": "Serverless middleware enforcing responsible-AI compliance on LLM applications — PII detection, bias screening, hate-speech filtering, and RAG-powered policy enforcement on top of Azure OpenAI.", + "12_desc": "Cloud Carbon Intelligence platform estimating CO2e emissions from Azure infrastructure with AI-powered reduction recommendations. Clean Architecture, Azure AI Search semantic factor lookup, 88 automated tests. Built for EU CSRD Scope 3 compliance." }, "skills": { "label": "04 — SKILLS", diff --git a/src/messages/en.json b/src/messages/en.json index 77adefc..ea546fb 100644 --- a/src/messages/en.json +++ b/src/messages/en.json @@ -1,8 +1,8 @@ { "metadata": { "title": "Pyae Sone Kyaw | AI Engineer · Full-Stack · Backend Systems", - "description": "Portfolio of Pyae Sone Kyaw (Seon) — Full-Stack AI Engineer at Siloett.AI (Station F, Paris). Full-stack AI systems (Python · FastAPI · Next.js · LLM evaluation harnesses), with deep backend roots (Java 21 · Spring Boot 3 · Kafka · microservices) and cloud data engineering on AWS, Snowflake, Databricks. Open to AI / Full-Stack / Backend roles in FR / DE / UK.", - "ogDescription": "Full-Stack AI Engineer @ Siloett.AI (Station F, Paris) · Full-stack AI systems · Backend (Java 21, Spring Boot, Kafka) · Cloud Data (AWS, Snowflake, Databricks). Open to AI / Full-Stack / Backend roles in FR / DE / UK." + "description": "Portfolio of Pyae Sone Kyaw (Seon) — Founder & Full-Stack / AI Engineer at Ekkhara, building EdTech for Myanmar (incl. SpeakProof). Full-stack AI systems (Python · FastAPI · Next.js · LLM evaluation harnesses), with deep backend roots (Java 21 · Spring Boot 3 · Kafka · microservices) and cloud data engineering on AWS, Snowflake, Databricks. Open to AI / Full-Stack / Backend roles in FR / DE / UK.", + "ogDescription": "Founder & Full-Stack / AI Engineer @ Ekkhara · ex-Siloett.AI (Station F, Paris) · Full-stack AI systems · Backend (Java 21, Spring Boot, Kafka) · Cloud Data (AWS, Snowflake, Databricks). Open to AI / Full-Stack / Backend roles in FR / DE / UK." }, "nav": { "about": "ABOUT", @@ -14,7 +14,7 @@ "resume": "RÉSUMÉ" }, "hero": { - "subtitle": "FULL-STACK AI ENGINEER · STATION F · PARIS", + "subtitle": "FOUNDER · FULL-STACK & AI ENGINEER · PARIS", "specialties": "AI Engineering · Full-Stack Systems · Backend & Cloud Data", "openTo": "OPEN TO AI / FULL-STACK / BACKEND ROLES · FR / DE / UK", "viewWork": "VIEW WORK", @@ -26,7 +26,7 @@ "heading": "AI Engineer · Full-Stack ·", "headingEm": "Backend Systems", "quote": "AI Engineer · Full-Stack · Backend Systems — building production-grade software at the intersection of telecom, healthcare, and finance, across Asia and Europe.", - "p1": "Currently a Full-Stack AI Engineer at Siloett.AI (Station F, Paris), where I architect end-to-end Generative AI systems on Azure with FastAPI, Azure Functions, and React/TypeScript.", + "p1": "Currently the founder of Ekkhara, a self-funded software & AI studio building EdTech for Myanmar — most recently SpeakProof, a Telegram-native TOEFL practice bot that works without a VPN. Before this I was a Full-Stack AI Engineer at Siloett.AI (Station F, Paris), architecting end-to-end Generative AI systems on Azure with FastAPI and React/TypeScript.", "p2": "Beyond AI, my engineering portfolio spans backend systems — Java 21, Spring Boot 3.5, Kafka, microservices — and cloud data engineering on AWS, Snowflake, Databricks, dbt, and Airflow. Telecom domain depth includes CDR pipelines, SMPP gateways, and Diameter Credit-Control.", "p3": "Dual Master's degrees from Telecom SudParis (Paris) and AIT (Bangkok), plus 5+ years shipping production software across healthcare, RegTech, telecom, and smart-city domains.", "p4": "Currently exploring AI Engineer, Full-Stack, and Backend Engineer roles across France, Germany, and the UK. If you're hiring or know of a fit — let's talk.", @@ -40,37 +40,43 @@ "label": "02 — EXPERIENCE", "heading": "Where I've", "headingEm": "Built & Learned", - "0_job": "Full-Stack AI Engineer", - "0_badge": "AI Safety & Compliance · Station F · Paris", - "0_date": "Jun 2025 — May 2026", - "0_pt0": "Architected and built an end-to-end Generative AI platform from zero — LLM orchestration, RAG pipelines, and a production React/TypeScript frontend with Python (FastAPI) and Azure Functions serverless backend", - "0_pt1": "Designed and implemented responsible-AI validation layers including content-safety filters, bias-detection checks, and compliance guardrails ensuring all AI-generated outputs meet regulatory and ethical standards", - "0_pt2": "Built AI safety and IP compliance systems including audit logging, provenance tracking, and output attribution pipelines — ensuring traceable and accountable AI output lifecycles", - "0_pt3": "Developed prompt-engineering and LLM evaluation frameworks using Azure OpenAI GPT-4o and LangChain, with systematic fine-tuning to optimise domain accuracy across compliance use cases", - "1_job": "Data Science / Cloud Data Engineer", - "1_badge": "Station F · Paris", - "1_date": "Jul 2024 — Dec 2025", - "1_pt0": "Designed a cloud-based batch data processing pipeline using Microsoft Azure Batch and Docker for urban mobility analytics", - "1_pt1": "Automated Computer Vision and Bluetooth sensor workflows enabling scalable, real-time smart city insights", - "1_pt2": "Delivered production analytics dashboards adopted by city government and transport stakeholders", - "2_job": "Research & Back-End Engineer", - "2_badge": "Computer Vision · Backend AI", - "2_date": "Aug 2023 — Jul 2024", - "2_pt0": "Engineered back-end services and data pipelines for a research lab delivering applied-AI capabilities to partner organisations — productionising computer-vision and NLP research behind Python APIs", - "2_pt1": "Built a complete English–Myanmar machine translation system on a 10K gold-labelled WikiHow corpus — owning dataset construction, model training, evaluation, and deployment behind a public API", - "2_pt2": "Developed novel research prototypes in computer vision and multilingual NLP, plus the back-end infrastructure to serve them — turning lab research into reproducible, deployable tools", + "0_job": "Founder & Full-Stack / AI Engineer", + "0_badge": "Founder · EdTech for Myanmar", + "0_date": "May 2026 — Present", + "0_pt0": "Founded Ekkhara, a self-funded software & AI studio building EdTech products for Myanmar — taking each from idea to live product and owning architecture, backend, AI, and front-end end-to-end.", + "0_pt1": "Built SpeakProof, a TOEFL speaking & English-practice bot that runs entirely inside Telegram — letting Myanmar learners train for the TOEFL computer-based test from an app they already use daily, with no VPN needed despite the country's internet restrictions.", + "0_pt2": "Engineer the full stack behind each product — Python / FastAPI services, LLM-driven feedback and scoring, and conversational UX — shipping AI tools that reach users where access and infrastructure are constrained.", + "1_job": "Full-Stack AI Engineer", + "1_badge": "AI Safety & Compliance · Station F · Paris", + "1_date": "Jun 2025 — May 2026", + "1_pt0": "Architected and built an end-to-end Generative AI platform from zero — LLM orchestration, RAG pipelines, and a production React/TypeScript frontend with Python (FastAPI) and Azure Functions serverless backend", + "1_pt1": "Designed and implemented responsible-AI validation layers including content-safety filters, bias-detection checks, and compliance guardrails ensuring all AI-generated outputs meet regulatory and ethical standards", + "1_pt2": "Built AI safety and IP compliance systems including audit logging, provenance tracking, and output attribution pipelines — ensuring traceable and accountable AI output lifecycles", + "1_pt3": "Developed prompt-engineering and LLM evaluation frameworks using Azure OpenAI GPT-4o and LangChain, with systematic fine-tuning to optimise domain accuracy across compliance use cases", + "2_job": "Data Science / Cloud Data Engineer", + "2_badge": "Station F · Paris", + "2_date": "Jul 2024 — Dec 2025", + "2_pt0": "Designed a cloud-based batch data processing pipeline using Microsoft Azure Batch and Docker for urban mobility analytics", + "2_pt1": "Automated Computer Vision and Bluetooth sensor workflows enabling scalable, real-time smart city insights", + "2_pt2": "Delivered production analytics dashboards adopted by city government and transport stakeholders", "3_job": "Research & Back-End Engineer", - "3_badge": "Applied-AI Lab · Backend", - "3_date": "Jan 2023 — Aug 2023", - "3_pt0": "Built an NLP paraphrasing tool end-to-end at a research lab providing applied-AI services to companies — from model development to back-end API", - "3_pt1": "Engineered the data layer — cleaning and structuring training datasets — and optimised training workflows, improving model accuracy by 15%", - "3_pt2": "Owned back-end operations for the lab's AI tooling, strengthening data-management and R&D engineering practice", - "4_job": "Software Engineer (Web)", - "4_badge": "Full-Stack Web · UN Agency", - "4_date": "Jan 2021 — Dec 2022", - "4_pt0": "Built full-stack web applications for a United Nations agency (FAO) — internal data dashboards and public-facing portals delivering agricultural and food-security programme data to staff and field teams", - "4_pt1": "Engineered field data-collection tools and the back-end APIs behind them, letting field officers capture, validate, and sync programme data into centralised reporting systems", - "4_pt2": "Owned features end-to-end across the stack — React/Next.js + TypeScript front-ends with Python and PHP/CMS back-ends — from data model and REST API to deployed UI" + "3_badge": "Computer Vision · Backend AI", + "3_date": "Aug 2023 — Jul 2024", + "3_pt0": "Engineered back-end services and data pipelines for a research lab delivering applied-AI capabilities to partner organisations — productionising computer-vision and NLP research behind Python APIs", + "3_pt1": "Built a complete English–Myanmar machine translation system on a 10K gold-labelled WikiHow corpus — owning dataset construction, model training, evaluation, and deployment behind a public API", + "3_pt2": "Developed novel research prototypes in computer vision and multilingual NLP, plus the back-end infrastructure to serve them — turning lab research into reproducible, deployable tools", + "4_job": "Research & Back-End Engineer", + "4_badge": "Applied-AI Lab · Backend", + "4_date": "Jan 2023 — Aug 2023", + "4_pt0": "Built an NLP paraphrasing tool end-to-end at a research lab providing applied-AI services to companies — from model development to back-end API", + "4_pt1": "Engineered the data layer — cleaning and structuring training datasets — and optimised training workflows, improving model accuracy by 15%", + "4_pt2": "Owned back-end operations for the lab's AI tooling, strengthening data-management and R&D engineering practice", + "5_job": "Software Engineer (Web)", + "5_badge": "Full-Stack Web · UN Agency", + "5_date": "Jan 2021 — Dec 2022", + "5_pt0": "Built full-stack web applications for a United Nations agency (FAO) — internal data dashboards and public-facing portals delivering agricultural and food-security programme data to staff and field teams", + "5_pt1": "Engineered field data-collection tools and the back-end APIs behind them, letting field officers capture, validate, and sync programme data into centralised reporting systems", + "5_pt2": "Owned features end-to-end across the stack — React/Next.js + TypeScript front-ends with Python and PHP/CMS back-ends — from data model and REST API to deployed UI" }, "projects": { "label": "03 — PROJECTS", @@ -83,19 +89,21 @@ "demo": "DEMO", "gh": "GH", "liveAtVercel": "LIVE ON VERCEL", + "liveAtTelegram": "LIVE ON TELEGRAM", "openSourceOnGithub": "OPEN-SOURCE ON GITHUB", - "0_desc": "Real-time European grid lakehouse on AWS — probabilistic load forecasting (DeepAR / quantile loss) and stochastic optimisation for battery flexibility decisions. Medallion architecture on S3 + Iceberg, MSK Kafka streaming, dbt models, Airflow orchestration, MLflow tracking. Cloud Data Engineering portfolio piece.", - "1_desc": "Event-driven Call Detail Record ingestion, rating, and reconciliation pipeline simulating an MVNO billing back-end. Idempotent Kafka consumers, Spring Boot 3.5 microservices, MySQL for rated CDRs, MongoDB for raw events, Docker Compose for local infra. Built around real telecom domain models (3GPP TS 32.298).", - "2_desc": "End-to-end CSRD/ESRS sustainability data pipeline — Claude/Mistral GenAI extraction from sustainability reports with page-level audit lineage, Snowflake warehouse (validated) + DuckDB local dev, dbt transformations, Airflow orchestration. Built for EU corporate sustainability reporting compliance.", - "3_desc": "AI-powered blood test interpretation for personalised supplement guidance — competing at Haleon VivaTech 2026. OCR ingestion of French lab reports, validated biomarker classification, longitudinal tracking, and supplement recommendations grounded in clinical evidence. Real-data moat through partner lab integrations.", - "4_desc": "From-scratch ReAct Agent Observatory — observe, debug, and benchmark LLM agents with a built-in 8-type failure taxonomy (hallucinated tools, malformed actions, context overflow, goal drift, …) and multi-provider eval harness (Groq, OpenAI, Anthropic, Google, Ollama). Composite scoring (answer + tools + efficiency + reliability), Clean Architecture FastAPI + PostgreSQL backend, Next.js 16 frontend with real-time SSE streaming. 50+ benchmark cases, 81 tests.", - "5_desc": "Real-World Evidence platform for vaccine research — full-stack application for ingesting, analyzing, and visualizing vaccine safety and efficacy data from real-world sources at scale. Built at Siloett.AI for healthcare and life-sciences buyers.", - "6_desc": "Diameter Credit-Control Server (Gy / RFC 4006 / App-Id 4) for real-time prepaid mobile billing. Idempotent partial debits, jdiameter 1.7.x stack, designed against TRANSATEL/MVNO production patterns.", - "7_desc": "Java SMPP v3.4 gateway bridging inbound SMS (submit_sm) to RabbitMQ for downstream processing. Spring Boot 3.5 + jsmpp 3.0, dockerised, designed for MVNO and telecom messaging platforms.", - "8_desc": "Real-time urban mobility analytics on TimescaleDB + PostGIS + Uber H3. Spring Boot ingestion, Kafka stream processing, Server-Sent Events for live dashboards. Smart-city back-end blueprint.", - "9_desc": "Reference implementation of the BCBS 239 risk-data-aggregation lakehouse pattern on Databricks + Delta Lake + Unity Catalog + dbt-databricks. MIT-licensed, synthetic data only — banking risk-data engineering portfolio piece.", - "10_desc": "Serverless middleware enforcing responsible-AI compliance on LLM applications — PII detection, bias screening, hate-speech filtering, and RAG-powered policy enforcement on top of Azure OpenAI.", - "11_desc": "Cloud Carbon Intelligence platform estimating CO2e emissions from Azure infrastructure with AI-powered reduction recommendations. Clean Architecture, Azure AI Search semantic factor lookup, 88 automated tests. Built for EU CSRD Scope 3 compliance." + "0_desc": "Telegram-native TOEFL speaking & English-practice bot for Myanmar learners — drill toward the TOEFL computer-based test inside an app people already use daily, with zero VPN needed despite nationwide internet restrictions. LLM-powered speaking feedback and scoring on a Python / FastAPI backend. An Ekkhara EdTech product.", + "1_desc": "Real-time European grid lakehouse on AWS — probabilistic load forecasting (DeepAR / quantile loss) and stochastic optimisation for battery flexibility decisions. Medallion architecture on S3 + Iceberg, MSK Kafka streaming, dbt models, Airflow orchestration, MLflow tracking. Cloud Data Engineering portfolio piece.", + "2_desc": "Event-driven Call Detail Record ingestion, rating, and reconciliation pipeline simulating an MVNO billing back-end. Idempotent Kafka consumers, Spring Boot 3.5 microservices, MySQL for rated CDRs, MongoDB for raw events, Docker Compose for local infra. Built around real telecom domain models (3GPP TS 32.298).", + "3_desc": "End-to-end CSRD/ESRS sustainability data pipeline — Claude/Mistral GenAI extraction from sustainability reports with page-level audit lineage, Snowflake warehouse (validated) + DuckDB local dev, dbt transformations, Airflow orchestration. Built for EU corporate sustainability reporting compliance.", + "4_desc": "AI-powered blood test interpretation for personalised supplement guidance — competing at Haleon VivaTech 2026. OCR ingestion of French lab reports, validated biomarker classification, longitudinal tracking, and supplement recommendations grounded in clinical evidence. Real-data moat through partner lab integrations.", + "5_desc": "From-scratch ReAct Agent Observatory — observe, debug, and benchmark LLM agents with a built-in 8-type failure taxonomy (hallucinated tools, malformed actions, context overflow, goal drift, …) and multi-provider eval harness (Groq, OpenAI, Anthropic, Google, Ollama). Composite scoring (answer + tools + efficiency + reliability), Clean Architecture FastAPI + PostgreSQL backend, Next.js 16 frontend with real-time SSE streaming. 50+ benchmark cases, 81 tests.", + "6_desc": "Real-World Evidence platform for vaccine research — full-stack application for ingesting, analyzing, and visualizing vaccine safety and efficacy data from real-world sources at scale. Built at Siloett.AI for healthcare and life-sciences buyers.", + "7_desc": "Diameter Credit-Control Server (Gy / RFC 4006 / App-Id 4) for real-time prepaid mobile billing. Idempotent partial debits, jdiameter 1.7.x stack, designed against TRANSATEL/MVNO production patterns.", + "8_desc": "Java SMPP v3.4 gateway bridging inbound SMS (submit_sm) to RabbitMQ for downstream processing. Spring Boot 3.5 + jsmpp 3.0, dockerised, designed for MVNO and telecom messaging platforms.", + "9_desc": "Real-time urban mobility analytics on TimescaleDB + PostGIS + Uber H3. Spring Boot ingestion, Kafka stream processing, Server-Sent Events for live dashboards. Smart-city back-end blueprint.", + "10_desc": "Reference implementation of the BCBS 239 risk-data-aggregation lakehouse pattern on Databricks + Delta Lake + Unity Catalog + dbt-databricks. MIT-licensed, synthetic data only — banking risk-data engineering portfolio piece.", + "11_desc": "Serverless middleware enforcing responsible-AI compliance on LLM applications — PII detection, bias screening, hate-speech filtering, and RAG-powered policy enforcement on top of Azure OpenAI.", + "12_desc": "Cloud Carbon Intelligence platform estimating CO2e emissions from Azure infrastructure with AI-powered reduction recommendations. Clean Architecture, Azure AI Search semantic factor lookup, 88 automated tests. Built for EU CSRD Scope 3 compliance." }, "skills": { "label": "04 — SKILLS", diff --git a/src/messages/es.json b/src/messages/es.json index fd278ed..24b57fb 100644 --- a/src/messages/es.json +++ b/src/messages/es.json @@ -14,7 +14,7 @@ "resume": "CURRÍCULUM" }, "hero": { - "subtitle": "FULL-STACK AI ENGINEER · STATION F · PARIS", + "subtitle": "FUNDADOR · INGENIERO FULL-STACK & IA · PARÍS", "specialties": "AI Engineering · Full-Stack Systems · Backend & Cloud Data", "openTo": "OPEN TO AI / FULL-STACK / BACKEND ROLES · FR / DE / UK", "viewWork": "VER TRABAJO", @@ -26,7 +26,7 @@ "heading": "AI Engineer · Full-Stack ·", "headingEm": "Backend Systems", "quote": "AI Engineer · Full-Stack · Backend Systems — building production-grade software at the intersection of telecom, healthcare, and finance, across Asia and Europe.", - "p1": "Currently a Full-Stack AI Engineer at Siloett.AI (Station F, Paris), where I architect end-to-end Generative AI systems on Azure with FastAPI, Azure Functions, and React/TypeScript.", + "p1": "Actualmente fundador de Ekkhara, un estudio de software e IA autofinanciado que crea EdTech para Myanmar — más recientemente SpeakProof, un bot de práctica de TOEFL nativo de Telegram que funciona sin VPN. Antes fui Ingeniero Full-Stack de IA en Siloett.AI (Station F, París), diseñando sistemas de IA generativa de extremo a extremo en Azure con FastAPI y React/TypeScript.", "p2": "Beyond AI, my engineering portfolio spans backend systems — Java 21, Spring Boot 3.5, Kafka, microservices — and cloud data engineering on AWS, Snowflake, Databricks, dbt, and Airflow. Telecom domain depth includes CDR pipelines, SMPP gateways, and Diameter Credit-Control.", "p3": "Dual Master's degrees from Telecom SudParis (Paris) and AIT (Bangkok), plus 5+ years shipping production software across healthcare, RegTech, telecom, and smart-city domains.", "p4": "Currently exploring AI Engineer, Full-Stack, and Backend Engineer roles across France, Germany, and the UK. If you're hiring or know of a fit — let's talk.", @@ -40,37 +40,43 @@ "label": "02 — EXPERIENCE", "heading": "Donde he", "headingEm": "Construido y Aprendido", - "0_job": "Ingeniero de IA Full-Stack", - "0_badge": "AI Safety & Compliance · Station F · París", - "0_date": "Jun 2025 — May 2026", - "0_pt0": "Diseñé y construí una plataforma de AI Generativa de extremo a extremo desde cero — orquestación de LLM, pipelines de RAG, y un frontend de producción en React/TypeScript con backend serverless en Python (FastAPI) y Azure Functions", - "0_pt1": "Diseñé e implementé capas de validación de AI responsable incluyendo filtros de seguridad de contenido, detección de sesgos y barreras de cumplimiento que aseguran que todas las salidas generadas por AI cumplan estándares regulatorios y éticos", - "0_pt2": "Construí sistemas de seguridad de AI y cumplimiento de propiedad intelectual incluyendo registro de auditoría, seguimiento de procedencia y pipelines de atribución de salidas — asegurando ciclos de vida de salida de AI trazables y responsables", - "0_pt3": "Desarrollé frameworks de prompt engineering y evaluación de LLM usando Azure OpenAI GPT-4o y LangChain, con ajuste fino sistemático para optimizar la precisión del dominio en casos de uso de cumplimiento", - "1_job": "Ciencia de Datos / Ingeniero de Datos Cloud", - "1_badge": "Station F · París", - "1_date": "Jul 2024 — Dec 2025", - "1_pt0": "Diseñé un pipeline de procesamiento de datos por lotes basado en la nube usando Microsoft Azure Batch y Docker para analítica de movilidad urbana", - "1_pt1": "Automaticé flujos de trabajo de Visión por Computadora y sensores Bluetooth permitiendo perspectivas escalables en tiempo real para ciudades inteligentes", - "1_pt2": "Entregué dashboards de analítica de producción adoptados por gobiernos municipales y actores del transporte", - "2_job": "Ingeniero de Investigación y Back-End", - "2_badge": "Visión por Computador · IA Backend", - "2_date": "Aug 2023 — Jul 2024", - "2_pt0": "Desarrollé servicios back-end y pipelines de datos para un laboratorio de investigación que ofrece capacidades de IA aplicada a organizaciones asociadas — llevando a producción investigación de visión por computador y NLP detrás de APIs en Python", - "2_pt1": "Construí un sistema completo de traducción automática inglés–birmano sobre un corpus WikiHow de 10K ejemplos etiquetados manualmente — desde la construcción del dataset hasta el entrenamiento, la evaluación y el despliegue tras una API pública", - "2_pt2": "Desarrollé prototipos de investigación novedosos en visión por computador y NLP multilingüe, junto con la infraestructura back-end para servirlos — convirtiendo la investigación del laboratorio en herramientas reproducibles y desplegables", + "0_job": "Fundador & Ingeniero Full-Stack / IA", + "0_badge": "Fundador · EdTech para Myanmar", + "0_date": "May 2026 — Present", + "0_pt0": "Fundé Ekkhara, un estudio de software e IA autofinanciado que crea productos EdTech para Myanmar — llevando cada uno de la idea al producto en vivo y asumiendo la arquitectura, el backend, la IA y el frontend de extremo a extremo.", + "0_pt1": "Creé SpeakProof, un bot de expresión oral para el TOEFL y práctica de inglés que funciona por completo dentro de Telegram — permitiendo a los estudiantes de Myanmar prepararse para el TOEFL (examen por computadora) desde una app que ya usan a diario, sin necesidad de VPN pese a las restricciones de internet del país.", + "0_pt2": "Desarrollo de toda la stack detrás de cada producto — servicios Python / FastAPI, feedback y puntuación impulsados por LLM y UX conversacional — entregando herramientas de IA que llegan a los usuarios donde el acceso y la infraestructura son limitados.", + "1_job": "Ingeniero de IA Full-Stack", + "1_badge": "AI Safety & Compliance · Station F · París", + "1_date": "Jun 2025 — May 2026", + "1_pt0": "Diseñé y construí una plataforma de AI Generativa de extremo a extremo desde cero — orquestación de LLM, pipelines de RAG, y un frontend de producción en React/TypeScript con backend serverless en Python (FastAPI) y Azure Functions", + "1_pt1": "Diseñé e implementé capas de validación de AI responsable incluyendo filtros de seguridad de contenido, detección de sesgos y barreras de cumplimiento que aseguran que todas las salidas generadas por AI cumplan estándares regulatorios y éticos", + "1_pt2": "Construí sistemas de seguridad de AI y cumplimiento de propiedad intelectual incluyendo registro de auditoría, seguimiento de procedencia y pipelines de atribución de salidas — asegurando ciclos de vida de salida de AI trazables y responsables", + "1_pt3": "Desarrollé frameworks de prompt engineering y evaluación de LLM usando Azure OpenAI GPT-4o y LangChain, con ajuste fino sistemático para optimizar la precisión del dominio en casos de uso de cumplimiento", + "2_job": "Ciencia de Datos / Ingeniero de Datos Cloud", + "2_badge": "Station F · París", + "2_date": "Jul 2024 — Dec 2025", + "2_pt0": "Diseñé un pipeline de procesamiento de datos por lotes basado en la nube usando Microsoft Azure Batch y Docker para analítica de movilidad urbana", + "2_pt1": "Automaticé flujos de trabajo de Visión por Computadora y sensores Bluetooth permitiendo perspectivas escalables en tiempo real para ciudades inteligentes", + "2_pt2": "Entregué dashboards de analítica de producción adoptados por gobiernos municipales y actores del transporte", "3_job": "Ingeniero de Investigación y Back-End", - "3_badge": "Laboratorio de IA Aplicada · Backend", - "3_date": "Jan 2023 — Aug 2023", - "3_pt0": "Construí de extremo a extremo una herramienta de paráfrasis NLP en un laboratorio de investigación que ofrece servicios de IA aplicada a empresas — del modelo a la API back-end", - "3_pt1": "Diseñé la capa de datos — limpieza y estructuración de datasets de entrenamiento — y optimicé los flujos de entrenamiento, mejorando la precisión del modelo en un 15 %", - "3_pt2": "Responsable de las operaciones back-end de las herramientas de IA del laboratorio, fortaleciendo la gestión de datos y la práctica de ingeniería de I+D", - "4_job": "Ingeniero de Software (Web)", - "4_badge": "Full-Stack Web · Agencia de la ONU", - "4_date": "Jan 2021 — Dec 2022", - "4_pt0": "Desarrollé aplicaciones web full-stack para una agencia de la ONU (FAO): paneles de datos internos y portales públicos que entregaban datos de programas de agricultura y seguridad alimentaria al personal y a los equipos de campo", - "4_pt1": "Diseñé herramientas de recolección de datos de campo y las APIs back-end que las respaldan, permitiendo a los oficiales de campo capturar, validar y sincronizar datos de programas en sistemas centralizados de reporte", - "4_pt2": "Responsable de funcionalidades de extremo a extremo en todo el stack — front-ends en React/Next.js + TypeScript con back-ends en Python y PHP/CMS — desde el modelo de datos y la REST API hasta la UI desplegada" + "3_badge": "Visión por Computador · IA Backend", + "3_date": "Aug 2023 — Jul 2024", + "3_pt0": "Desarrollé servicios back-end y pipelines de datos para un laboratorio de investigación que ofrece capacidades de IA aplicada a organizaciones asociadas — llevando a producción investigación de visión por computador y NLP detrás de APIs en Python", + "3_pt1": "Construí un sistema completo de traducción automática inglés–birmano sobre un corpus WikiHow de 10K ejemplos etiquetados manualmente — desde la construcción del dataset hasta el entrenamiento, la evaluación y el despliegue tras una API pública", + "3_pt2": "Desarrollé prototipos de investigación novedosos en visión por computador y NLP multilingüe, junto con la infraestructura back-end para servirlos — convirtiendo la investigación del laboratorio en herramientas reproducibles y desplegables", + "4_job": "Ingeniero de Investigación y Back-End", + "4_badge": "Laboratorio de IA Aplicada · Backend", + "4_date": "Jan 2023 — Aug 2023", + "4_pt0": "Construí de extremo a extremo una herramienta de paráfrasis NLP en un laboratorio de investigación que ofrece servicios de IA aplicada a empresas — del modelo a la API back-end", + "4_pt1": "Diseñé la capa de datos — limpieza y estructuración de datasets de entrenamiento — y optimicé los flujos de entrenamiento, mejorando la precisión del modelo en un 15 %", + "4_pt2": "Responsable de las operaciones back-end de las herramientas de IA del laboratorio, fortaleciendo la gestión de datos y la práctica de ingeniería de I+D", + "5_job": "Ingeniero de Software (Web)", + "5_badge": "Full-Stack Web · Agencia de la ONU", + "5_date": "Jan 2021 — Dec 2022", + "5_pt0": "Desarrollé aplicaciones web full-stack para una agencia de la ONU (FAO): paneles de datos internos y portales públicos que entregaban datos de programas de agricultura y seguridad alimentaria al personal y a los equipos de campo", + "5_pt1": "Diseñé herramientas de recolección de datos de campo y las APIs back-end que las respaldan, permitiendo a los oficiales de campo capturar, validar y sincronizar datos de programas en sistemas centralizados de reporte", + "5_pt2": "Responsable de funcionalidades de extremo a extremo en todo el stack — front-ends en React/Next.js + TypeScript con back-ends en Python y PHP/CMS — desde el modelo de datos y la REST API hasta la UI desplegada" }, "projects": { "label": "03 — PROJECTS", @@ -83,19 +89,21 @@ "demo": "DEMO", "gh": "GH", "liveAtVercel": "LIVE ON VERCEL", + "liveAtTelegram": "LIVE ON TELEGRAM", "openSourceOnGithub": "OPEN-SOURCE ON GITHUB", - "0_desc": "Real-time European grid lakehouse on AWS — probabilistic load forecasting (DeepAR / quantile loss) and stochastic optimisation for battery flexibility decisions. Medallion architecture on S3 + Iceberg, MSK Kafka streaming, dbt models, Airflow orchestration, MLflow tracking. Cloud Data Engineering portfolio piece.", - "1_desc": "Event-driven Call Detail Record ingestion, rating, and reconciliation pipeline simulating an MVNO billing back-end. Idempotent Kafka consumers, Spring Boot 3.5 microservices, MySQL for rated CDRs, MongoDB for raw events, Docker Compose for local infra. Built around real telecom domain models (3GPP TS 32.298).", - "2_desc": "End-to-end CSRD/ESRS sustainability data pipeline — Claude/Mistral GenAI extraction from sustainability reports with page-level audit lineage, Snowflake warehouse (validated) + DuckDB local dev, dbt transformations, Airflow orchestration. Built for EU corporate sustainability reporting compliance.", - "3_desc": "AI-powered blood test interpretation for personalised supplement guidance — competing at Haleon VivaTech 2026. OCR ingestion of French lab reports, validated biomarker classification, longitudinal tracking, and supplement recommendations grounded in clinical evidence. Real-data moat through partner lab integrations.", - "4_desc": "From-scratch ReAct Agent Observatory — observe, debug, and benchmark LLM agents with a built-in 8-type failure taxonomy (hallucinated tools, malformed actions, context overflow, goal drift, …) and multi-provider eval harness (Groq, OpenAI, Anthropic, Google, Ollama). Composite scoring (answer + tools + efficiency + reliability), Clean Architecture FastAPI + PostgreSQL backend, Next.js 16 frontend with real-time SSE streaming. 50+ benchmark cases, 81 tests.", - "5_desc": "Real-World Evidence platform for vaccine research — full-stack application for ingesting, analyzing, and visualizing vaccine safety and efficacy data from real-world sources at scale. Built at Siloett.AI for healthcare and life-sciences buyers.", - "6_desc": "Diameter Credit-Control Server (Gy / RFC 4006 / App-Id 4) for real-time prepaid mobile billing. Idempotent partial debits, jdiameter 1.7.x stack, designed against TRANSATEL/MVNO production patterns.", - "7_desc": "Java SMPP v3.4 gateway bridging inbound SMS (submit_sm) to RabbitMQ for downstream processing. Spring Boot 3.5 + jsmpp 3.0, dockerised, designed for MVNO and telecom messaging platforms.", - "8_desc": "Real-time urban mobility analytics on TimescaleDB + PostGIS + Uber H3. Spring Boot ingestion, Kafka stream processing, Server-Sent Events for live dashboards. Smart-city back-end blueprint.", - "9_desc": "Reference implementation of the BCBS 239 risk-data-aggregation lakehouse pattern on Databricks + Delta Lake + Unity Catalog + dbt-databricks. MIT-licensed, synthetic data only — banking risk-data engineering portfolio piece.", - "10_desc": "Serverless middleware enforcing responsible-AI compliance on LLM applications — PII detection, bias screening, hate-speech filtering, and RAG-powered policy enforcement on top of Azure OpenAI.", - "11_desc": "Cloud Carbon Intelligence platform estimating CO2e emissions from Azure infrastructure with AI-powered reduction recommendations. Clean Architecture, Azure AI Search semantic factor lookup, 88 automated tests. Built for EU CSRD Scope 3 compliance." + "0_desc": "Telegram-native TOEFL speaking & English-practice bot for Myanmar learners — drill toward the TOEFL computer-based test inside an app people already use daily, with zero VPN needed despite nationwide internet restrictions. LLM-powered speaking feedback and scoring on a Python / FastAPI backend. An Ekkhara EdTech product.", + "1_desc": "Real-time European grid lakehouse on AWS — probabilistic load forecasting (DeepAR / quantile loss) and stochastic optimisation for battery flexibility decisions. Medallion architecture on S3 + Iceberg, MSK Kafka streaming, dbt models, Airflow orchestration, MLflow tracking. Cloud Data Engineering portfolio piece.", + "2_desc": "Event-driven Call Detail Record ingestion, rating, and reconciliation pipeline simulating an MVNO billing back-end. Idempotent Kafka consumers, Spring Boot 3.5 microservices, MySQL for rated CDRs, MongoDB for raw events, Docker Compose for local infra. Built around real telecom domain models (3GPP TS 32.298).", + "3_desc": "End-to-end CSRD/ESRS sustainability data pipeline — Claude/Mistral GenAI extraction from sustainability reports with page-level audit lineage, Snowflake warehouse (validated) + DuckDB local dev, dbt transformations, Airflow orchestration. Built for EU corporate sustainability reporting compliance.", + "4_desc": "AI-powered blood test interpretation for personalised supplement guidance — competing at Haleon VivaTech 2026. OCR ingestion of French lab reports, validated biomarker classification, longitudinal tracking, and supplement recommendations grounded in clinical evidence. Real-data moat through partner lab integrations.", + "5_desc": "From-scratch ReAct Agent Observatory — observe, debug, and benchmark LLM agents with a built-in 8-type failure taxonomy (hallucinated tools, malformed actions, context overflow, goal drift, …) and multi-provider eval harness (Groq, OpenAI, Anthropic, Google, Ollama). Composite scoring (answer + tools + efficiency + reliability), Clean Architecture FastAPI + PostgreSQL backend, Next.js 16 frontend with real-time SSE streaming. 50+ benchmark cases, 81 tests.", + "6_desc": "Real-World Evidence platform for vaccine research — full-stack application for ingesting, analyzing, and visualizing vaccine safety and efficacy data from real-world sources at scale. Built at Siloett.AI for healthcare and life-sciences buyers.", + "7_desc": "Diameter Credit-Control Server (Gy / RFC 4006 / App-Id 4) for real-time prepaid mobile billing. Idempotent partial debits, jdiameter 1.7.x stack, designed against TRANSATEL/MVNO production patterns.", + "8_desc": "Java SMPP v3.4 gateway bridging inbound SMS (submit_sm) to RabbitMQ for downstream processing. Spring Boot 3.5 + jsmpp 3.0, dockerised, designed for MVNO and telecom messaging platforms.", + "9_desc": "Real-time urban mobility analytics on TimescaleDB + PostGIS + Uber H3. Spring Boot ingestion, Kafka stream processing, Server-Sent Events for live dashboards. Smart-city back-end blueprint.", + "10_desc": "Reference implementation of the BCBS 239 risk-data-aggregation lakehouse pattern on Databricks + Delta Lake + Unity Catalog + dbt-databricks. MIT-licensed, synthetic data only — banking risk-data engineering portfolio piece.", + "11_desc": "Serverless middleware enforcing responsible-AI compliance on LLM applications — PII detection, bias screening, hate-speech filtering, and RAG-powered policy enforcement on top of Azure OpenAI.", + "12_desc": "Cloud Carbon Intelligence platform estimating CO2e emissions from Azure infrastructure with AI-powered reduction recommendations. Clean Architecture, Azure AI Search semantic factor lookup, 88 automated tests. Built for EU CSRD Scope 3 compliance." }, "skills": { "label": "04 — SKILLS", diff --git a/src/messages/fr.json b/src/messages/fr.json index 6b13593..680702f 100644 --- a/src/messages/fr.json +++ b/src/messages/fr.json @@ -14,7 +14,7 @@ "resume": "CV" }, "hero": { - "subtitle": "FULL-STACK AI ENGINEER · STATION F · PARIS", + "subtitle": "FONDATEUR · INGÉNIEUR FULL-STACK & IA · PARIS", "specialties": "AI Engineering · Full-Stack Systems · Backend & Cloud Data", "openTo": "OPEN TO AI / FULL-STACK / BACKEND ROLES · FR / DE / UK", "viewWork": "VOIR MES TRAVAUX", @@ -26,7 +26,7 @@ "heading": "AI Engineer · Full-Stack ·", "headingEm": "Backend Systems", "quote": "AI Engineer · Full-Stack · Backend Systems — building production-grade software at the intersection of telecom, healthcare, and finance, across Asia and Europe.", - "p1": "Currently a Full-Stack AI Engineer at Siloett.AI (Station F, Paris), where I architect end-to-end Generative AI systems on Azure with FastAPI, Azure Functions, and React/TypeScript.", + "p1": "Actuellement fondateur d'Ekkhara, un studio logiciel & IA autofinancé qui développe des produits EdTech pour le Myanmar — dont récemment SpeakProof, un bot d'entraînement au TOEFL natif sur Telegram qui fonctionne sans VPN. Auparavant, Ingénieur Full-Stack IA chez Siloett.AI (Station F, Paris), où je concevais des systèmes d'IA générative de bout en bout sur Azure avec FastAPI et React/TypeScript.", "p2": "Beyond AI, my engineering portfolio spans backend systems — Java 21, Spring Boot 3.5, Kafka, microservices — and cloud data engineering on AWS, Snowflake, Databricks, dbt, and Airflow. Telecom domain depth includes CDR pipelines, SMPP gateways, and Diameter Credit-Control.", "p3": "Dual Master's degrees from Telecom SudParis (Paris) and AIT (Bangkok), plus 5+ years shipping production software across healthcare, RegTech, telecom, and smart-city domains.", "p4": "Currently exploring AI Engineer, Full-Stack, and Backend Engineer roles across France, Germany, and the UK. If you're hiring or know of a fit — let's talk.", @@ -40,37 +40,43 @@ "label": "02 — EXPERIENCE", "heading": "Là où j'ai", "headingEm": "construit et appris", - "0_job": "Ingénieur IA Full-Stack", - "0_badge": "AI Safety & Compliance · Station F · Paris", - "0_date": "Jun 2025 — May 2026", - "0_pt0": "Conçu et développé une plateforme d'IA Générative de bout en bout à partir de zéro — orchestration LLM, pipelines RAG, et un frontend React/TypeScript en production avec un backend serverless Python (FastAPI) et Azure Functions", - "0_pt1": "Conçu et implémenté des couches de validation d'IA responsable incluant des filtres de sécurité de contenu, des vérifications de détection de biais et des garde-fous de conformité garantissant que toutes les sorties IA respectent les standards réglementaires et éthiques", - "0_pt2": "Développé des systèmes de sécurité IA et de conformité PI incluant la journalisation d'audit, le suivi de provenance et les pipelines d'attribution des sorties — assurant des cycles de vie de sorties IA traçables et responsables", - "0_pt3": "Développé des frameworks de prompt engineering et d'évaluation LLM utilisant Azure OpenAI GPT-4o et LangChain, avec un fine-tuning systématique pour optimiser la précision selon les cas d'usage de conformité", - "1_job": "Data Science / Ingénieur Cloud Data", - "1_badge": "Station F · Paris", - "1_date": "Jul 2024 — Dec 2025", - "1_pt0": "Conçu un pipeline de traitement batch de données dans le cloud avec Microsoft Azure Batch et Docker pour l'analyse de mobilité urbaine", - "1_pt1": "Automatisé les workflows de Computer Vision et de capteurs Bluetooth permettant des analyses smart city évolutives en temps réel", - "1_pt2": "Livré des tableaux de bord analytiques en production adoptés par les collectivités et les parties prenantes du transport", - "2_job": "Ingénieur Recherche & Back-End", - "2_badge": "Vision par ordinateur · IA Backend", - "2_date": "Aug 2023 — Jul 2024", - "2_pt0": "Conçu les services back-end et les pipelines de données d'un laboratoire de recherche fournissant des capacités d'IA appliquée à des organisations partenaires — industrialisation de travaux de vision par ordinateur et de NLP derrière des API Python", - "2_pt1": "Construit un système complet de traduction automatique anglais–birman sur un corpus WikiHow de 10K exemples labellisés manuellement — de la construction du dataset à l'entraînement, l'évaluation et le déploiement derrière une API publique", - "2_pt2": "Développé des prototypes de recherche inédits en vision par ordinateur et NLP multilingue, ainsi que l'infrastructure back-end pour les servir — transformant la recherche du laboratoire en outils reproductibles et déployables", + "0_job": "Fondateur & Ingénieur Full-Stack / IA", + "0_badge": "Fondateur · EdTech pour le Myanmar", + "0_date": "May 2026 — Present", + "0_pt0": "Création d'Ekkhara, un studio logiciel & IA autofinancé qui développe des produits EdTech pour le Myanmar — chaque produit mené de l'idée au lancement, en maîtrisant l'architecture, le back-end, l'IA et le front-end de bout en bout.", + "0_pt1": "Développement de SpeakProof, un bot d'expression orale TOEFL et d'entraînement à l'anglais qui fonctionne entièrement dans Telegram — permettant aux apprenants du Myanmar de se préparer au TOEFL (épreuve sur ordinateur) depuis une application qu'ils utilisent déjà chaque jour, sans VPN malgré les restrictions d'accès à Internet dans le pays.", + "0_pt2": "Conception de toute la stack derrière chaque produit — services Python / FastAPI, retours et notation pilotés par LLM, et UX conversationnelle — pour livrer des outils d'IA qui atteignent les utilisateurs là où l'accès et l'infrastructure sont limités.", + "1_job": "Ingénieur IA Full-Stack", + "1_badge": "AI Safety & Compliance · Station F · Paris", + "1_date": "Jun 2025 — May 2026", + "1_pt0": "Conçu et développé une plateforme d'IA Générative de bout en bout à partir de zéro — orchestration LLM, pipelines RAG, et un frontend React/TypeScript en production avec un backend serverless Python (FastAPI) et Azure Functions", + "1_pt1": "Conçu et implémenté des couches de validation d'IA responsable incluant des filtres de sécurité de contenu, des vérifications de détection de biais et des garde-fous de conformité garantissant que toutes les sorties IA respectent les standards réglementaires et éthiques", + "1_pt2": "Développé des systèmes de sécurité IA et de conformité PI incluant la journalisation d'audit, le suivi de provenance et les pipelines d'attribution des sorties — assurant des cycles de vie de sorties IA traçables et responsables", + "1_pt3": "Développé des frameworks de prompt engineering et d'évaluation LLM utilisant Azure OpenAI GPT-4o et LangChain, avec un fine-tuning systématique pour optimiser la précision selon les cas d'usage de conformité", + "2_job": "Data Science / Ingénieur Cloud Data", + "2_badge": "Station F · Paris", + "2_date": "Jul 2024 — Dec 2025", + "2_pt0": "Conçu un pipeline de traitement batch de données dans le cloud avec Microsoft Azure Batch et Docker pour l'analyse de mobilité urbaine", + "2_pt1": "Automatisé les workflows de Computer Vision et de capteurs Bluetooth permettant des analyses smart city évolutives en temps réel", + "2_pt2": "Livré des tableaux de bord analytiques en production adoptés par les collectivités et les parties prenantes du transport", "3_job": "Ingénieur Recherche & Back-End", - "3_badge": "Labo IA Appliquée · Backend", - "3_date": "Jan 2023 — Aug 2023", - "3_pt0": "Développé de bout en bout un outil de paraphrase NLP dans un laboratoire de recherche fournissant des services d'IA appliquée aux entreprises — du modèle à l'API back-end", - "3_pt1": "Conçu la couche de données — nettoyage et structuration des datasets d'entraînement — et optimisé les workflows d'entraînement, améliorant la précision du modèle de 15 %", - "3_pt2": "Pris en charge les opérations back-end des outils IA du laboratoire, renforçant la gestion des données et les pratiques d'ingénierie R&D", - "4_job": "Ingénieur Logiciel (Web)", - "4_badge": "Full-Stack Web · Agence de l'ONU", - "4_date": "Jan 2021 — Dec 2022", - "4_pt0": "Développé des applications web full-stack pour une agence de l'ONU (FAO) — tableaux de bord de données internes et portails publics diffusant les données des programmes d'agriculture et de sécurité alimentaire au personnel et aux équipes de terrain", - "4_pt1": "Conçu des outils de collecte de données sur le terrain et les APIs back-end associées, permettant aux agents de terrain de saisir, valider et synchroniser les données des programmes vers des systèmes de reporting centralisés", - "4_pt2": "Pris en charge des fonctionnalités de bout en bout sur toute la stack — front-ends React/Next.js + TypeScript avec back-ends Python et PHP/CMS — du modèle de données et de la REST API jusqu'à l'UI déployée" + "3_badge": "Vision par ordinateur · IA Backend", + "3_date": "Aug 2023 — Jul 2024", + "3_pt0": "Conçu les services back-end et les pipelines de données d'un laboratoire de recherche fournissant des capacités d'IA appliquée à des organisations partenaires — industrialisation de travaux de vision par ordinateur et de NLP derrière des API Python", + "3_pt1": "Construit un système complet de traduction automatique anglais–birman sur un corpus WikiHow de 10K exemples labellisés manuellement — de la construction du dataset à l'entraînement, l'évaluation et le déploiement derrière une API publique", + "3_pt2": "Développé des prototypes de recherche inédits en vision par ordinateur et NLP multilingue, ainsi que l'infrastructure back-end pour les servir — transformant la recherche du laboratoire en outils reproductibles et déployables", + "4_job": "Ingénieur Recherche & Back-End", + "4_badge": "Labo IA Appliquée · Backend", + "4_date": "Jan 2023 — Aug 2023", + "4_pt0": "Développé de bout en bout un outil de paraphrase NLP dans un laboratoire de recherche fournissant des services d'IA appliquée aux entreprises — du modèle à l'API back-end", + "4_pt1": "Conçu la couche de données — nettoyage et structuration des datasets d'entraînement — et optimisé les workflows d'entraînement, améliorant la précision du modèle de 15 %", + "4_pt2": "Pris en charge les opérations back-end des outils IA du laboratoire, renforçant la gestion des données et les pratiques d'ingénierie R&D", + "5_job": "Ingénieur Logiciel (Web)", + "5_badge": "Full-Stack Web · Agence de l'ONU", + "5_date": "Jan 2021 — Dec 2022", + "5_pt0": "Développé des applications web full-stack pour une agence de l'ONU (FAO) — tableaux de bord de données internes et portails publics diffusant les données des programmes d'agriculture et de sécurité alimentaire au personnel et aux équipes de terrain", + "5_pt1": "Conçu des outils de collecte de données sur le terrain et les APIs back-end associées, permettant aux agents de terrain de saisir, valider et synchroniser les données des programmes vers des systèmes de reporting centralisés", + "5_pt2": "Pris en charge des fonctionnalités de bout en bout sur toute la stack — front-ends React/Next.js + TypeScript avec back-ends Python et PHP/CMS — du modèle de données et de la REST API jusqu'à l'UI déployée" }, "projects": { "label": "03 — PROJECTS", @@ -83,19 +89,21 @@ "demo": "DÉMO", "gh": "GH", "liveAtVercel": "LIVE ON VERCEL", + "liveAtTelegram": "LIVE ON TELEGRAM", "openSourceOnGithub": "OPEN-SOURCE ON GITHUB", - "0_desc": "Real-time European grid lakehouse on AWS — probabilistic load forecasting (DeepAR / quantile loss) and stochastic optimisation for battery flexibility decisions. Medallion architecture on S3 + Iceberg, MSK Kafka streaming, dbt models, Airflow orchestration, MLflow tracking. Cloud Data Engineering portfolio piece.", - "1_desc": "Event-driven Call Detail Record ingestion, rating, and reconciliation pipeline simulating an MVNO billing back-end. Idempotent Kafka consumers, Spring Boot 3.5 microservices, MySQL for rated CDRs, MongoDB for raw events, Docker Compose for local infra. Built around real telecom domain models (3GPP TS 32.298).", - "2_desc": "End-to-end CSRD/ESRS sustainability data pipeline — Claude/Mistral GenAI extraction from sustainability reports with page-level audit lineage, Snowflake warehouse (validated) + DuckDB local dev, dbt transformations, Airflow orchestration. Built for EU corporate sustainability reporting compliance.", - "3_desc": "AI-powered blood test interpretation for personalised supplement guidance — competing at Haleon VivaTech 2026. OCR ingestion of French lab reports, validated biomarker classification, longitudinal tracking, and supplement recommendations grounded in clinical evidence. Real-data moat through partner lab integrations.", - "4_desc": "From-scratch ReAct Agent Observatory — observe, debug, and benchmark LLM agents with a built-in 8-type failure taxonomy (hallucinated tools, malformed actions, context overflow, goal drift, …) and multi-provider eval harness (Groq, OpenAI, Anthropic, Google, Ollama). Composite scoring (answer + tools + efficiency + reliability), Clean Architecture FastAPI + PostgreSQL backend, Next.js 16 frontend with real-time SSE streaming. 50+ benchmark cases, 81 tests.", - "5_desc": "Real-World Evidence platform for vaccine research — full-stack application for ingesting, analyzing, and visualizing vaccine safety and efficacy data from real-world sources at scale. Built at Siloett.AI for healthcare and life-sciences buyers.", - "6_desc": "Diameter Credit-Control Server (Gy / RFC 4006 / App-Id 4) for real-time prepaid mobile billing. Idempotent partial debits, jdiameter 1.7.x stack, designed against TRANSATEL/MVNO production patterns.", - "7_desc": "Java SMPP v3.4 gateway bridging inbound SMS (submit_sm) to RabbitMQ for downstream processing. Spring Boot 3.5 + jsmpp 3.0, dockerised, designed for MVNO and telecom messaging platforms.", - "8_desc": "Real-time urban mobility analytics on TimescaleDB + PostGIS + Uber H3. Spring Boot ingestion, Kafka stream processing, Server-Sent Events for live dashboards. Smart-city back-end blueprint.", - "9_desc": "Reference implementation of the BCBS 239 risk-data-aggregation lakehouse pattern on Databricks + Delta Lake + Unity Catalog + dbt-databricks. MIT-licensed, synthetic data only — banking risk-data engineering portfolio piece.", - "10_desc": "Serverless middleware enforcing responsible-AI compliance on LLM applications — PII detection, bias screening, hate-speech filtering, and RAG-powered policy enforcement on top of Azure OpenAI.", - "11_desc": "Cloud Carbon Intelligence platform estimating CO2e emissions from Azure infrastructure with AI-powered reduction recommendations. Clean Architecture, Azure AI Search semantic factor lookup, 88 automated tests. Built for EU CSRD Scope 3 compliance." + "0_desc": "Telegram-native TOEFL speaking & English-practice bot for Myanmar learners — drill toward the TOEFL computer-based test inside an app people already use daily, with zero VPN needed despite nationwide internet restrictions. LLM-powered speaking feedback and scoring on a Python / FastAPI backend. An Ekkhara EdTech product.", + "1_desc": "Real-time European grid lakehouse on AWS — probabilistic load forecasting (DeepAR / quantile loss) and stochastic optimisation for battery flexibility decisions. Medallion architecture on S3 + Iceberg, MSK Kafka streaming, dbt models, Airflow orchestration, MLflow tracking. Cloud Data Engineering portfolio piece.", + "2_desc": "Event-driven Call Detail Record ingestion, rating, and reconciliation pipeline simulating an MVNO billing back-end. Idempotent Kafka consumers, Spring Boot 3.5 microservices, MySQL for rated CDRs, MongoDB for raw events, Docker Compose for local infra. Built around real telecom domain models (3GPP TS 32.298).", + "3_desc": "End-to-end CSRD/ESRS sustainability data pipeline — Claude/Mistral GenAI extraction from sustainability reports with page-level audit lineage, Snowflake warehouse (validated) + DuckDB local dev, dbt transformations, Airflow orchestration. Built for EU corporate sustainability reporting compliance.", + "4_desc": "AI-powered blood test interpretation for personalised supplement guidance — competing at Haleon VivaTech 2026. OCR ingestion of French lab reports, validated biomarker classification, longitudinal tracking, and supplement recommendations grounded in clinical evidence. Real-data moat through partner lab integrations.", + "5_desc": "From-scratch ReAct Agent Observatory — observe, debug, and benchmark LLM agents with a built-in 8-type failure taxonomy (hallucinated tools, malformed actions, context overflow, goal drift, …) and multi-provider eval harness (Groq, OpenAI, Anthropic, Google, Ollama). Composite scoring (answer + tools + efficiency + reliability), Clean Architecture FastAPI + PostgreSQL backend, Next.js 16 frontend with real-time SSE streaming. 50+ benchmark cases, 81 tests.", + "6_desc": "Real-World Evidence platform for vaccine research — full-stack application for ingesting, analyzing, and visualizing vaccine safety and efficacy data from real-world sources at scale. Built at Siloett.AI for healthcare and life-sciences buyers.", + "7_desc": "Diameter Credit-Control Server (Gy / RFC 4006 / App-Id 4) for real-time prepaid mobile billing. Idempotent partial debits, jdiameter 1.7.x stack, designed against TRANSATEL/MVNO production patterns.", + "8_desc": "Java SMPP v3.4 gateway bridging inbound SMS (submit_sm) to RabbitMQ for downstream processing. Spring Boot 3.5 + jsmpp 3.0, dockerised, designed for MVNO and telecom messaging platforms.", + "9_desc": "Real-time urban mobility analytics on TimescaleDB + PostGIS + Uber H3. Spring Boot ingestion, Kafka stream processing, Server-Sent Events for live dashboards. Smart-city back-end blueprint.", + "10_desc": "Reference implementation of the BCBS 239 risk-data-aggregation lakehouse pattern on Databricks + Delta Lake + Unity Catalog + dbt-databricks. MIT-licensed, synthetic data only — banking risk-data engineering portfolio piece.", + "11_desc": "Serverless middleware enforcing responsible-AI compliance on LLM applications — PII detection, bias screening, hate-speech filtering, and RAG-powered policy enforcement on top of Azure OpenAI.", + "12_desc": "Cloud Carbon Intelligence platform estimating CO2e emissions from Azure infrastructure with AI-powered reduction recommendations. Clean Architecture, Azure AI Search semantic factor lookup, 88 automated tests. Built for EU CSRD Scope 3 compliance." }, "skills": { "label": "04 — SKILLS", diff --git a/src/messages/ja.json b/src/messages/ja.json index 497e207..33987a7 100644 --- a/src/messages/ja.json +++ b/src/messages/ja.json @@ -14,7 +14,7 @@ "resume": "履歴書" }, "hero": { - "subtitle": "FULL-STACK AI ENGINEER · STATION F · PARIS", + "subtitle": "創業者 · フルスタック & AI エンジニア · パリ", "specialties": "AI Engineering · Full-Stack Systems · Backend & Cloud Data", "openTo": "OPEN TO AI / FULL-STACK / BACKEND ROLES · FR / DE / UK", "viewWork": "実績を見る", @@ -26,7 +26,7 @@ "heading": "AI Engineer · Full-Stack ·", "headingEm": "Backend Systems", "quote": "AI Engineer · Full-Stack · Backend Systems — building production-grade software at the intersection of telecom, healthcare, and finance, across Asia and Europe.", - "p1": "Currently a Full-Stack AI Engineer at Siloett.AI (Station F, Paris), where I architect end-to-end Generative AI systems on Azure with FastAPI, Azure Functions, and React/TypeScript.", + "p1": "現在は Ekkhara の創業者として、自己資金でミャンマー向けの EdTech を開発——直近のプロダクトは、VPN なしで使える Telegram ネイティブの TOEFL 練習ボット「SpeakProof」。それ以前は Siloett.AI(パリ Station F)でフルスタック AI エンジニアとして、FastAPI と React/TypeScript を用いて Azure 上のエンドツーエンドの生成 AI システムを設計。", "p2": "Beyond AI, my engineering portfolio spans backend systems — Java 21, Spring Boot 3.5, Kafka, microservices — and cloud data engineering on AWS, Snowflake, Databricks, dbt, and Airflow. Telecom domain depth includes CDR pipelines, SMPP gateways, and Diameter Credit-Control.", "p3": "Dual Master's degrees from Telecom SudParis (Paris) and AIT (Bangkok), plus 5+ years shipping production software across healthcare, RegTech, telecom, and smart-city domains.", "p4": "Currently exploring AI Engineer, Full-Stack, and Backend Engineer roles across France, Germany, and the UK. If you're hiring or know of a fit — let's talk.", @@ -40,37 +40,43 @@ "label": "02 — EXPERIENCE", "heading": "構築と学びの", "headingEm": "軌跡", - "0_job": "フルスタックAIエンジニア", - "0_badge": "AI安全性＆コンプライアンス · Station F · パリ", - "0_date": "Jun 2025 — May 2026", - "0_pt0": "ゼロからエンドツーエンドの生成AIプラットフォームを設計・構築 — LLMオーケストレーション、RAGパイプライン、React/TypeScriptフロントエンドとPython（FastAPI）およびAzure Functionsサーバーレスバックエンドの本番環境", - "0_pt1": "コンテンツ安全フィルター、バイアス検出チェック、コンプライアンスガードレールなど、責任あるAIバリデーションレイヤーを設計・実装し、AIが生成するすべての出力が規制・倫理基準を満たすことを保証", - "0_pt2": "監査ログ、来歴追跡、出力帰属パイプラインなどのAI安全性とIP準拠システムを構築 — 追跡可能で説明責任のあるAI出力ライフサイクルを保証", - "0_pt3": "Azure OpenAI GPT-4oとLangChainを使用したプロンプトエンジニアリングとLLM評価フレームワークを開発し、コンプライアンスユースケース全体のドメイン精度を最適化するための体系的なファインチューニングを実施", - "1_job": "データサイエンス / クラウドデータエンジニア", - "1_badge": "Station F · パリ", - "1_date": "Jul 2024 — Dec 2025", - "1_pt0": "Microsoft Azure BatchとDockerを使用した都市モビリティ分析のためのクラウドベースのバッチデータ処理パイプラインを設計", - "1_pt1": "コンピュータビジョンとBluetoothセンサーのワークフローを自動化し、スケーラブルなリアルタイムスマートシティインサイトを実現", - "1_pt2": "市政府と交通関係者に採用された本番分析ダッシュボードを提供", - "2_job": "リサーチ＆バックエンドエンジニア", - "2_badge": "コンピュータビジョン · バックエンドAI", - "2_date": "Aug 2023 — Jul 2024", - "2_pt0": "パートナー企業に応用AI機能を提供する研究室向けに、バックエンドサービスとデータパイプラインを構築 — コンピュータビジョンとNLPの研究をPython APIとして本番運用化", - "2_pt1": "手作業で構築した1万件のgold-labeled WikiHowコーパスを用い、英語–ミャンマー語の機械翻訳システムを一から構築 — データセット構築、モデル学習、評価、公開APIへのデプロイまでを担当", - "2_pt2": "コンピュータビジョンと多言語NLPにおける新規研究プロトタイプと、それらを提供するバックエンド基盤を開発 — 研究室の成果を再現可能でデプロイ可能なツールへ", + "0_job": "創業者 & フルスタック / AI エンジニア", + "0_badge": "創業者 · ミャンマー向け EdTech", + "0_date": "May 2026 — Present", + "0_pt0": "自己資金によるソフトウェア & AI スタジオ Ekkhara を創業し、ミャンマー向けの EdTech プロダクトを開発——各プロダクトをアイデアからリリースまで導き、アーキテクチャ・バックエンド・AI・フロントエンドを一貫して担当。", + "0_pt1": "Telegram 内で完結する TOEFL スピーキング & 英語練習ボット「SpeakProof」を開発——ミャンマーの学習者が、国のインターネット規制下でも VPN なしで、日常的に使うアプリから TOEFL(コンピューター版)対策を行えるように。", + "0_pt2": "各プロダクトの背後にあるフルスタックを担当——Python / FastAPI サービス、LLM によるフィードバックとスコアリング、会話型 UX——アクセスやインフラが限られた環境のユーザーにも届く AI ツールを提供。", + "1_job": "フルスタックAIエンジニア", + "1_badge": "AI安全性＆コンプライアンス · Station F · パリ", + "1_date": "Jun 2025 — May 2026", + "1_pt0": "ゼロからエンドツーエンドの生成AIプラットフォームを設計・構築 — LLMオーケストレーション、RAGパイプライン、React/TypeScriptフロントエンドとPython（FastAPI）およびAzure Functionsサーバーレスバックエンドの本番環境", + "1_pt1": "コンテンツ安全フィルター、バイアス検出チェック、コンプライアンスガードレールなど、責任あるAIバリデーションレイヤーを設計・実装し、AIが生成するすべての出力が規制・倫理基準を満たすことを保証", + "1_pt2": "監査ログ、来歴追跡、出力帰属パイプラインなどのAI安全性とIP準拠システムを構築 — 追跡可能で説明責任のあるAI出力ライフサイクルを保証", + "1_pt3": "Azure OpenAI GPT-4oとLangChainを使用したプロンプトエンジニアリングとLLM評価フレームワークを開発し、コンプライアンスユースケース全体のドメイン精度を最適化するための体系的なファインチューニングを実施", + "2_job": "データサイエンス / クラウドデータエンジニア", + "2_badge": "Station F · パリ", + "2_date": "Jul 2024 — Dec 2025", + "2_pt0": "Microsoft Azure BatchとDockerを使用した都市モビリティ分析のためのクラウドベースのバッチデータ処理パイプラインを設計", + "2_pt1": "コンピュータビジョンとBluetoothセンサーのワークフローを自動化し、スケーラブルなリアルタイムスマートシティインサイトを実現", + "2_pt2": "市政府と交通関係者に採用された本番分析ダッシュボードを提供", "3_job": "リサーチ＆バックエンドエンジニア", - "3_badge": "応用AIラボ · バックエンド", - "3_date": "Jan 2023 — Aug 2023", - "3_pt0": "企業に応用AIサービスを提供する研究室で、NLP言い換えツールをモデルからバックエンドAPIまで一貫して構築", - "3_pt1": "データ層を構築 — 学習データセットのクレンジングと構造化 — し、学習ワークフローを最適化してモデル精度を15%向上", - "3_pt2": "研究室のAIツールのバックエンド運用を担当し、データ管理とR&Dエンジニアリングの実践力を強化", - "4_job": "ソフトウェアエンジニア（Web）", - "4_badge": "フルスタックWeb · 国連機関", - "4_date": "Jan 2021 — Dec 2022", - "4_pt0": "国連機関（FAO）向けにフルスタックWebアプリケーションを構築 — 農業・食料安全保障プログラムのデータを職員や現場チームに提供する社内データダッシュボードと公開ポータルを開発", - "4_pt1": "現場データ収集ツールとその背後のバックエンドAPIを設計し、現場担当者がプログラムデータを取得・検証し、中央のレポーティングシステムへ同期できるようにした", - "4_pt2": "スタック全体で機能をエンドツーエンドに担当 — React/Next.js + TypeScript のフロントエンドと Python・PHP/CMS のバックエンド — データモデルとREST APIからデプロイ済みのUIまで" + "3_badge": "コンピュータビジョン · バックエンドAI", + "3_date": "Aug 2023 — Jul 2024", + "3_pt0": "パートナー企業に応用AI機能を提供する研究室向けに、バックエンドサービスとデータパイプラインを構築 — コンピュータビジョンとNLPの研究をPython APIとして本番運用化", + "3_pt1": "手作業で構築した1万件のgold-labeled WikiHowコーパスを用い、英語–ミャンマー語の機械翻訳システムを一から構築 — データセット構築、モデル学習、評価、公開APIへのデプロイまでを担当", + "3_pt2": "コンピュータビジョンと多言語NLPにおける新規研究プロトタイプと、それらを提供するバックエンド基盤を開発 — 研究室の成果を再現可能でデプロイ可能なツールへ", + "4_job": "リサーチ＆バックエンドエンジニア", + "4_badge": "応用AIラボ · バックエンド", + "4_date": "Jan 2023 — Aug 2023", + "4_pt0": "企業に応用AIサービスを提供する研究室で、NLP言い換えツールをモデルからバックエンドAPIまで一貫して構築", + "4_pt1": "データ層を構築 — 学習データセットのクレンジングと構造化 — し、学習ワークフローを最適化してモデル精度を15%向上", + "4_pt2": "研究室のAIツールのバックエンド運用を担当し、データ管理とR&Dエンジニアリングの実践力を強化", + "5_job": "ソフトウェアエンジニア（Web）", + "5_badge": "フルスタックWeb · 国連機関", + "5_date": "Jan 2021 — Dec 2022", + "5_pt0": "国連機関（FAO）向けにフルスタックWebアプリケーションを構築 — 農業・食料安全保障プログラムのデータを職員や現場チームに提供する社内データダッシュボードと公開ポータルを開発", + "5_pt1": "現場データ収集ツールとその背後のバックエンドAPIを設計し、現場担当者がプログラムデータを取得・検証し、中央のレポーティングシステムへ同期できるようにした", + "5_pt2": "スタック全体で機能をエンドツーエンドに担当 — React/Next.js + TypeScript のフロントエンドと Python・PHP/CMS のバックエンド — データモデルとREST APIからデプロイ済みのUIまで" }, "projects": { "label": "03 — PROJECTS", @@ -83,19 +89,21 @@ "demo": "デモ", "gh": "GH", "liveAtVercel": "LIVE ON VERCEL", + "liveAtTelegram": "LIVE ON TELEGRAM", "openSourceOnGithub": "OPEN-SOURCE ON GITHUB", - "0_desc": "Real-time European grid lakehouse on AWS — probabilistic load forecasting (DeepAR / quantile loss) and stochastic optimisation for battery flexibility decisions. Medallion architecture on S3 + Iceberg, MSK Kafka streaming, dbt models, Airflow orchestration, MLflow tracking. Cloud Data Engineering portfolio piece.", - "1_desc": "Event-driven Call Detail Record ingestion, rating, and reconciliation pipeline simulating an MVNO billing back-end. Idempotent Kafka consumers, Spring Boot 3.5 microservices, MySQL for rated CDRs, MongoDB for raw events, Docker Compose for local infra. Built around real telecom domain models (3GPP TS 32.298).", - "2_desc": "End-to-end CSRD/ESRS sustainability data pipeline — Claude/Mistral GenAI extraction from sustainability reports with page-level audit lineage, Snowflake warehouse (validated) + DuckDB local dev, dbt transformations, Airflow orchestration. Built for EU corporate sustainability reporting compliance.", - "3_desc": "AI-powered blood test interpretation for personalised supplement guidance — competing at Haleon VivaTech 2026. OCR ingestion of French lab reports, validated biomarker classification, longitudinal tracking, and supplement recommendations grounded in clinical evidence. Real-data moat through partner lab integrations.", - "4_desc": "From-scratch ReAct Agent Observatory — observe, debug, and benchmark LLM agents with a built-in 8-type failure taxonomy (hallucinated tools, malformed actions, context overflow, goal drift, …) and multi-provider eval harness (Groq, OpenAI, Anthropic, Google, Ollama). Composite scoring (answer + tools + efficiency + reliability), Clean Architecture FastAPI + PostgreSQL backend, Next.js 16 frontend with real-time SSE streaming. 50+ benchmark cases, 81 tests.", - "5_desc": "Real-World Evidence platform for vaccine research — full-stack application for ingesting, analyzing, and visualizing vaccine safety and efficacy data from real-world sources at scale. Built at Siloett.AI for healthcare and life-sciences buyers.", - "6_desc": "Diameter Credit-Control Server (Gy / RFC 4006 / App-Id 4) for real-time prepaid mobile billing. Idempotent partial debits, jdiameter 1.7.x stack, designed against TRANSATEL/MVNO production patterns.", - "7_desc": "Java SMPP v3.4 gateway bridging inbound SMS (submit_sm) to RabbitMQ for downstream processing. Spring Boot 3.5 + jsmpp 3.0, dockerised, designed for MVNO and telecom messaging platforms.", - "8_desc": "Real-time urban mobility analytics on TimescaleDB + PostGIS + Uber H3. Spring Boot ingestion, Kafka stream processing, Server-Sent Events for live dashboards. Smart-city back-end blueprint.", - "9_desc": "Reference implementation of the BCBS 239 risk-data-aggregation lakehouse pattern on Databricks + Delta Lake + Unity Catalog + dbt-databricks. MIT-licensed, synthetic data only — banking risk-data engineering portfolio piece.", - "10_desc": "Serverless middleware enforcing responsible-AI compliance on LLM applications — PII detection, bias screening, hate-speech filtering, and RAG-powered policy enforcement on top of Azure OpenAI.", - "11_desc": "Cloud Carbon Intelligence platform estimating CO2e emissions from Azure infrastructure with AI-powered reduction recommendations. Clean Architecture, Azure AI Search semantic factor lookup, 88 automated tests. Built for EU CSRD Scope 3 compliance." + "0_desc": "Telegram-native TOEFL speaking & English-practice bot for Myanmar learners — drill toward the TOEFL computer-based test inside an app people already use daily, with zero VPN needed despite nationwide internet restrictions. LLM-powered speaking feedback and scoring on a Python / FastAPI backend. An Ekkhara EdTech product.", + "1_desc": "Real-time European grid lakehouse on AWS — probabilistic load forecasting (DeepAR / quantile loss) and stochastic optimisation for battery flexibility decisions. Medallion architecture on S3 + Iceberg, MSK Kafka streaming, dbt models, Airflow orchestration, MLflow tracking. Cloud Data Engineering portfolio piece.", + "2_desc": "Event-driven Call Detail Record ingestion, rating, and reconciliation pipeline simulating an MVNO billing back-end. Idempotent Kafka consumers, Spring Boot 3.5 microservices, MySQL for rated CDRs, MongoDB for raw events, Docker Compose for local infra. Built around real telecom domain models (3GPP TS 32.298).", + "3_desc": "End-to-end CSRD/ESRS sustainability data pipeline — Claude/Mistral GenAI extraction from sustainability reports with page-level audit lineage, Snowflake warehouse (validated) + DuckDB local dev, dbt transformations, Airflow orchestration. Built for EU corporate sustainability reporting compliance.", + "4_desc": "AI-powered blood test interpretation for personalised supplement guidance — competing at Haleon VivaTech 2026. OCR ingestion of French lab reports, validated biomarker classification, longitudinal tracking, and supplement recommendations grounded in clinical evidence. Real-data moat through partner lab integrations.", + "5_desc": "From-scratch ReAct Agent Observatory — observe, debug, and benchmark LLM agents with a built-in 8-type failure taxonomy (hallucinated tools, malformed actions, context overflow, goal drift, …) and multi-provider eval harness (Groq, OpenAI, Anthropic, Google, Ollama). Composite scoring (answer + tools + efficiency + reliability), Clean Architecture FastAPI + PostgreSQL backend, Next.js 16 frontend with real-time SSE streaming. 50+ benchmark cases, 81 tests.", + "6_desc": "Real-World Evidence platform for vaccine research — full-stack application for ingesting, analyzing, and visualizing vaccine safety and efficacy data from real-world sources at scale. Built at Siloett.AI for healthcare and life-sciences buyers.", + "7_desc": "Diameter Credit-Control Server (Gy / RFC 4006 / App-Id 4) for real-time prepaid mobile billing. Idempotent partial debits, jdiameter 1.7.x stack, designed against TRANSATEL/MVNO production patterns.", + "8_desc": "Java SMPP v3.4 gateway bridging inbound SMS (submit_sm) to RabbitMQ for downstream processing. Spring Boot 3.5 + jsmpp 3.0, dockerised, designed for MVNO and telecom messaging platforms.", + "9_desc": "Real-time urban mobility analytics on TimescaleDB + PostGIS + Uber H3. Spring Boot ingestion, Kafka stream processing, Server-Sent Events for live dashboards. Smart-city back-end blueprint.", + "10_desc": "Reference implementation of the BCBS 239 risk-data-aggregation lakehouse pattern on Databricks + Delta Lake + Unity Catalog + dbt-databricks. MIT-licensed, synthetic data only — banking risk-data engineering portfolio piece.", + "11_desc": "Serverless middleware enforcing responsible-AI compliance on LLM applications — PII detection, bias screening, hate-speech filtering, and RAG-powered policy enforcement on top of Azure OpenAI.", + "12_desc": "Cloud Carbon Intelligence platform estimating CO2e emissions from Azure infrastructure with AI-powered reduction recommendations. Clean Architecture, Azure AI Search semantic factor lookup, 88 automated tests. Built for EU CSRD Scope 3 compliance." }, "skills": { "label": "04 — SKILLS", diff --git a/src/messages/ko.json b/src/messages/ko.json index 8118d2b..5997328 100644 --- a/src/messages/ko.json +++ b/src/messages/ko.json @@ -14,7 +14,7 @@ "resume": "이력서" }, "hero": { - "subtitle": "FULL-STACK AI ENGINEER · STATION F · PARIS", + "subtitle": "창업자 · 풀스택 & AI 엔지니어 · 파리", "specialties": "AI Engineering · Full-Stack Systems · Backend & Cloud Data", "openTo": "OPEN TO AI / FULL-STACK / BACKEND ROLES · FR / DE / UK", "viewWork": "작업 보기", @@ -26,7 +26,7 @@ "heading": "AI Engineer · Full-Stack ·", "headingEm": "Backend Systems", "quote": "AI Engineer · Full-Stack · Backend Systems — building production-grade software at the intersection of telecom, healthcare, and finance, across Asia and Europe.", - "p1": "Currently a Full-Stack AI Engineer at Siloett.AI (Station F, Paris), where I architect end-to-end Generative AI systems on Azure with FastAPI, Azure Functions, and React/TypeScript.", + "p1": "현재 Ekkhara의 창업자로서 자기자본으로 미얀마를 위한 EdTech를 개발하고 있으며 — 가장 최근 제품은 VPN 없이 작동하는 Telegram 네이티브 TOEFL 연습 봇 SpeakProof입니다. 그전에는 Siloett.AI(파리 Station F)에서 풀스택 AI 엔지니어로 FastAPI와 React/TypeScript로 Azure 기반의 엔드투엔드 생성형 AI 시스템을 설계했습니다.", "p2": "Beyond AI, my engineering portfolio spans backend systems — Java 21, Spring Boot 3.5, Kafka, microservices — and cloud data engineering on AWS, Snowflake, Databricks, dbt, and Airflow. Telecom domain depth includes CDR pipelines, SMPP gateways, and Diameter Credit-Control.", "p3": "Dual Master's degrees from Telecom SudParis (Paris) and AIT (Bangkok), plus 5+ years shipping production software across healthcare, RegTech, telecom, and smart-city domains.", "p4": "Currently exploring AI Engineer, Full-Stack, and Backend Engineer roles across France, Germany, and the UK. If you're hiring or know of a fit — let's talk.", @@ -40,37 +40,43 @@ "label": "02 — EXPERIENCE", "heading": "구축하고", "headingEm": "배운 곳", - "0_job": "풀스택 AI 엔지니어", - "0_badge": "AI Safety & Compliance · Station F · 파리", - "0_date": "Jun 2025 — May 2026", - "0_pt0": "LLM 오케스트레이션, RAG 파이프라인, React/TypeScript 프론트엔드와 Python (FastAPI) 및 Azure Functions 서버리스 백엔드를 포함한 엔드투엔드 Generative AI 플랫폼을 처음부터 설계 및 구축", - "0_pt1": "콘텐츠 안전 필터, 편향 탐지 검사, 규정 준수 가드레일을 포함한 책임 있는 AI 검증 레이어를 설계 및 구현하여 모든 AI 생성 출력이 규제 및 윤리 기준을 충족하도록 보장", - "0_pt2": "감사 로깅, 출처 추적, 출력 귀속 파이프라인을 포함한 AI 안전 및 IP 규정 준수 시스템을 구축 — 추적 가능하고 책임 있는 AI 출력 수명 주기 보장", - "0_pt3": "Azure OpenAI GPT-4o와 LangChain을 활용한 프롬프트 엔지니어링 및 LLM 평가 프레임워크를 개발하고, 규정 준수 사례 전반에 걸쳐 도메인 정확도를 최적화하기 위한 체계적 파인튜닝 수행", - "1_job": "데이터 사이언스 / 클라우드 데이터 엔지니어", - "1_badge": "Station F · 파리", - "1_date": "Jul 2024 — Dec 2025", - "1_pt0": "도시 이동성 분석을 위한 Microsoft Azure Batch와 Docker를 활용한 클라우드 기반 배치 데이터 처리 파이프라인 설계", - "1_pt1": "확장 가능한 실시간 스마트 시티 인사이트를 가능하게 하는 Computer Vision 및 Bluetooth 센서 워크플로우 자동화", - "1_pt2": "시 정부 및 교통 관계자가 채택한 프로덕션 분석 대시보드 제공", - "2_job": "리서치 & 백엔드 엔지니어", - "2_badge": "컴퓨터 비전 · 백엔드 AI", - "2_date": "Aug 2023 — Jul 2024", - "2_pt0": "파트너 기업에 응용 AI 역량을 제공하는 연구실을 위해 백엔드 서비스와 데이터 파이프라인을 구축 — 컴퓨터 비전 및 NLP 연구를 Python API로 프로덕션화", - "2_pt1": "수작업으로 구축한 1만 건의 gold-labeled WikiHow 코퍼스를 기반으로 영어–미얀마어 기계 번역 시스템을 완성 — 데이터셋 구축, 모델 학습, 평가, 공개 API 배포까지 담당", - "2_pt2": "컴퓨터 비전과 다국어 NLP의 신규 연구 프로토타입과 이를 서비스하는 백엔드 인프라를 개발 — 연구실 연구를 재현 가능하고 배포 가능한 도구로 전환", + "0_job": "창업자 & 풀스택 / AI 엔지니어", + "0_badge": "창업자 · 미얀마를 위한 EdTech", + "0_date": "May 2026 — Present", + "0_pt0": "자기자본으로 운영되는 소프트웨어 & AI 스튜디오 Ekkhara를 창업하여 미얀마를 위한 EdTech 제품을 개발 — 각 제품을 아이디어부터 출시까지 이끌며 아키텍처, 백엔드, AI, 프런트엔드를 전 과정 담당.", + "0_pt1": "Telegram 안에서 완전히 동작하는 TOEFL 스피킹 & 영어 연습 봇 SpeakProof를 개발 — 미얀마 학습자가 인터넷 제한 속에서도 VPN 없이, 매일 쓰는 앱에서 TOEFL(컴퓨터 기반 시험)을 준비할 수 있도록.", + "0_pt2": "각 제품 뒤의 풀스택을 직접 구축 — Python / FastAPI 서비스, LLM 기반 피드백·채점, 대화형 UX — 접근성과 인프라가 제한된 환경의 사용자에게도 닿는 AI 도구를 출시.", + "1_job": "풀스택 AI 엔지니어", + "1_badge": "AI Safety & Compliance · Station F · 파리", + "1_date": "Jun 2025 — May 2026", + "1_pt0": "LLM 오케스트레이션, RAG 파이프라인, React/TypeScript 프론트엔드와 Python (FastAPI) 및 Azure Functions 서버리스 백엔드를 포함한 엔드투엔드 Generative AI 플랫폼을 처음부터 설계 및 구축", + "1_pt1": "콘텐츠 안전 필터, 편향 탐지 검사, 규정 준수 가드레일을 포함한 책임 있는 AI 검증 레이어를 설계 및 구현하여 모든 AI 생성 출력이 규제 및 윤리 기준을 충족하도록 보장", + "1_pt2": "감사 로깅, 출처 추적, 출력 귀속 파이프라인을 포함한 AI 안전 및 IP 규정 준수 시스템을 구축 — 추적 가능하고 책임 있는 AI 출력 수명 주기 보장", + "1_pt3": "Azure OpenAI GPT-4o와 LangChain을 활용한 프롬프트 엔지니어링 및 LLM 평가 프레임워크를 개발하고, 규정 준수 사례 전반에 걸쳐 도메인 정확도를 최적화하기 위한 체계적 파인튜닝 수행", + "2_job": "데이터 사이언스 / 클라우드 데이터 엔지니어", + "2_badge": "Station F · 파리", + "2_date": "Jul 2024 — Dec 2025", + "2_pt0": "도시 이동성 분석을 위한 Microsoft Azure Batch와 Docker를 활용한 클라우드 기반 배치 데이터 처리 파이프라인 설계", + "2_pt1": "확장 가능한 실시간 스마트 시티 인사이트를 가능하게 하는 Computer Vision 및 Bluetooth 센서 워크플로우 자동화", + "2_pt2": "시 정부 및 교통 관계자가 채택한 프로덕션 분석 대시보드 제공", "3_job": "리서치 & 백엔드 엔지니어", - "3_badge": "응용 AI 연구실 · 백엔드", - "3_date": "Jan 2023 — Aug 2023", - "3_pt0": "기업에 응용 AI 서비스를 제공하는 연구실에서 NLP 패러프레이징 도구를 모델부터 백엔드 API까지 엔드투엔드로 구축", - "3_pt1": "데이터 계층을 구축 — 학습 데이터셋 정제 및 구조화 — 하고 학습 워크플로를 최적화하여 모델 정확도를 15% 향상", - "3_pt2": "연구실 AI 도구의 백엔드 운영을 담당하며 데이터 관리와 R&D 엔지니어링 역량을 강화", - "4_job": "소프트웨어 엔지니어 (Web)", - "4_badge": "풀스택 웹 · UN 기관", - "4_date": "Jan 2021 — Dec 2022", - "4_pt0": "UN 기관(FAO)을 위한 풀스택 웹 애플리케이션 구축 — 농업 및 식량 안보 프로그램 데이터를 직원과 현장 팀에 제공하는 내부 데이터 대시보드와 공개 포털 개발", - "4_pt1": "현장 데이터 수집 도구와 이를 뒷받침하는 백엔드 API를 설계하여, 현장 담당자가 프로그램 데이터를 수집·검증하고 중앙 리포팅 시스템으로 동기화할 수 있도록 함", - "4_pt2": "스택 전반에 걸쳐 기능을 엔드투엔드로 담당 — React/Next.js + TypeScript 프런트엔드와 Python·PHP/CMS 백엔드 — 데이터 모델과 REST API부터 배포된 UI까지" + "3_badge": "컴퓨터 비전 · 백엔드 AI", + "3_date": "Aug 2023 — Jul 2024", + "3_pt0": "파트너 기업에 응용 AI 역량을 제공하는 연구실을 위해 백엔드 서비스와 데이터 파이프라인을 구축 — 컴퓨터 비전 및 NLP 연구를 Python API로 프로덕션화", + "3_pt1": "수작업으로 구축한 1만 건의 gold-labeled WikiHow 코퍼스를 기반으로 영어–미얀마어 기계 번역 시스템을 완성 — 데이터셋 구축, 모델 학습, 평가, 공개 API 배포까지 담당", + "3_pt2": "컴퓨터 비전과 다국어 NLP의 신규 연구 프로토타입과 이를 서비스하는 백엔드 인프라를 개발 — 연구실 연구를 재현 가능하고 배포 가능한 도구로 전환", + "4_job": "리서치 & 백엔드 엔지니어", + "4_badge": "응용 AI 연구실 · 백엔드", + "4_date": "Jan 2023 — Aug 2023", + "4_pt0": "기업에 응용 AI 서비스를 제공하는 연구실에서 NLP 패러프레이징 도구를 모델부터 백엔드 API까지 엔드투엔드로 구축", + "4_pt1": "데이터 계층을 구축 — 학습 데이터셋 정제 및 구조화 — 하고 학습 워크플로를 최적화하여 모델 정확도를 15% 향상", + "4_pt2": "연구실 AI 도구의 백엔드 운영을 담당하며 데이터 관리와 R&D 엔지니어링 역량을 강화", + "5_job": "소프트웨어 엔지니어 (Web)", + "5_badge": "풀스택 웹 · UN 기관", + "5_date": "Jan 2021 — Dec 2022", + "5_pt0": "UN 기관(FAO)을 위한 풀스택 웹 애플리케이션 구축 — 농업 및 식량 안보 프로그램 데이터를 직원과 현장 팀에 제공하는 내부 데이터 대시보드와 공개 포털 개발", + "5_pt1": "현장 데이터 수집 도구와 이를 뒷받침하는 백엔드 API를 설계하여, 현장 담당자가 프로그램 데이터를 수집·검증하고 중앙 리포팅 시스템으로 동기화할 수 있도록 함", + "5_pt2": "스택 전반에 걸쳐 기능을 엔드투엔드로 담당 — React/Next.js + TypeScript 프런트엔드와 Python·PHP/CMS 백엔드 — 데이터 모델과 REST API부터 배포된 UI까지" }, "projects": { "label": "03 — PROJECTS", @@ -83,19 +89,21 @@ "demo": "데모", "gh": "GH", "liveAtVercel": "LIVE ON VERCEL", + "liveAtTelegram": "LIVE ON TELEGRAM", "openSourceOnGithub": "OPEN-SOURCE ON GITHUB", - "0_desc": "Real-time European grid lakehouse on AWS — probabilistic load forecasting (DeepAR / quantile loss) and stochastic optimisation for battery flexibility decisions. Medallion architecture on S3 + Iceberg, MSK Kafka streaming, dbt models, Airflow orchestration, MLflow tracking. Cloud Data Engineering portfolio piece.", - "1_desc": "Event-driven Call Detail Record ingestion, rating, and reconciliation pipeline simulating an MVNO billing back-end. Idempotent Kafka consumers, Spring Boot 3.5 microservices, MySQL for rated CDRs, MongoDB for raw events, Docker Compose for local infra. Built around real telecom domain models (3GPP TS 32.298).", - "2_desc": "End-to-end CSRD/ESRS sustainability data pipeline — Claude/Mistral GenAI extraction from sustainability reports with page-level audit lineage, Snowflake warehouse (validated) + DuckDB local dev, dbt transformations, Airflow orchestration. Built for EU corporate sustainability reporting compliance.", - "3_desc": "AI-powered blood test interpretation for personalised supplement guidance — competing at Haleon VivaTech 2026. OCR ingestion of French lab reports, validated biomarker classification, longitudinal tracking, and supplement recommendations grounded in clinical evidence. Real-data moat through partner lab integrations.", - "4_desc": "From-scratch ReAct Agent Observatory — observe, debug, and benchmark LLM agents with a built-in 8-type failure taxonomy (hallucinated tools, malformed actions, context overflow, goal drift, …) and multi-provider eval harness (Groq, OpenAI, Anthropic, Google, Ollama). Composite scoring (answer + tools + efficiency + reliability), Clean Architecture FastAPI + PostgreSQL backend, Next.js 16 frontend with real-time SSE streaming. 50+ benchmark cases, 81 tests.", - "5_desc": "Real-World Evidence platform for vaccine research — full-stack application for ingesting, analyzing, and visualizing vaccine safety and efficacy data from real-world sources at scale. Built at Siloett.AI for healthcare and life-sciences buyers.", - "6_desc": "Diameter Credit-Control Server (Gy / RFC 4006 / App-Id 4) for real-time prepaid mobile billing. Idempotent partial debits, jdiameter 1.7.x stack, designed against TRANSATEL/MVNO production patterns.", - "7_desc": "Java SMPP v3.4 gateway bridging inbound SMS (submit_sm) to RabbitMQ for downstream processing. Spring Boot 3.5 + jsmpp 3.0, dockerised, designed for MVNO and telecom messaging platforms.", - "8_desc": "Real-time urban mobility analytics on TimescaleDB + PostGIS + Uber H3. Spring Boot ingestion, Kafka stream processing, Server-Sent Events for live dashboards. Smart-city back-end blueprint.", - "9_desc": "Reference implementation of the BCBS 239 risk-data-aggregation lakehouse pattern on Databricks + Delta Lake + Unity Catalog + dbt-databricks. MIT-licensed, synthetic data only — banking risk-data engineering portfolio piece.", - "10_desc": "Serverless middleware enforcing responsible-AI compliance on LLM applications — PII detection, bias screening, hate-speech filtering, and RAG-powered policy enforcement on top of Azure OpenAI.", - "11_desc": "Cloud Carbon Intelligence platform estimating CO2e emissions from Azure infrastructure with AI-powered reduction recommendations. Clean Architecture, Azure AI Search semantic factor lookup, 88 automated tests. Built for EU CSRD Scope 3 compliance." + "0_desc": "Telegram-native TOEFL speaking & English-practice bot for Myanmar learners — drill toward the TOEFL computer-based test inside an app people already use daily, with zero VPN needed despite nationwide internet restrictions. LLM-powered speaking feedback and scoring on a Python / FastAPI backend. An Ekkhara EdTech product.", + "1_desc": "Real-time European grid lakehouse on AWS — probabilistic load forecasting (DeepAR / quantile loss) and stochastic optimisation for battery flexibility decisions. Medallion architecture on S3 + Iceberg, MSK Kafka streaming, dbt models, Airflow orchestration, MLflow tracking. Cloud Data Engineering portfolio piece.", + "2_desc": "Event-driven Call Detail Record ingestion, rating, and reconciliation pipeline simulating an MVNO billing back-end. Idempotent Kafka consumers, Spring Boot 3.5 microservices, MySQL for rated CDRs, MongoDB for raw events, Docker Compose for local infra. Built around real telecom domain models (3GPP TS 32.298).", + "3_desc": "End-to-end CSRD/ESRS sustainability data pipeline — Claude/Mistral GenAI extraction from sustainability reports with page-level audit lineage, Snowflake warehouse (validated) + DuckDB local dev, dbt transformations, Airflow orchestration. Built for EU corporate sustainability reporting compliance.", + "4_desc": "AI-powered blood test interpretation for personalised supplement guidance — competing at Haleon VivaTech 2026. OCR ingestion of French lab reports, validated biomarker classification, longitudinal tracking, and supplement recommendations grounded in clinical evidence. Real-data moat through partner lab integrations.", + "5_desc": "From-scratch ReAct Agent Observatory — observe, debug, and benchmark LLM agents with a built-in 8-type failure taxonomy (hallucinated tools, malformed actions, context overflow, goal drift, …) and multi-provider eval harness (Groq, OpenAI, Anthropic, Google, Ollama). Composite scoring (answer + tools + efficiency + reliability), Clean Architecture FastAPI + PostgreSQL backend, Next.js 16 frontend with real-time SSE streaming. 50+ benchmark cases, 81 tests.", + "6_desc": "Real-World Evidence platform for vaccine research — full-stack application for ingesting, analyzing, and visualizing vaccine safety and efficacy data from real-world sources at scale. Built at Siloett.AI for healthcare and life-sciences buyers.", + "7_desc": "Diameter Credit-Control Server (Gy / RFC 4006 / App-Id 4) for real-time prepaid mobile billing. Idempotent partial debits, jdiameter 1.7.x stack, designed against TRANSATEL/MVNO production patterns.", + "8_desc": "Java SMPP v3.4 gateway bridging inbound SMS (submit_sm) to RabbitMQ for downstream processing. Spring Boot 3.5 + jsmpp 3.0, dockerised, designed for MVNO and telecom messaging platforms.", + "9_desc": "Real-time urban mobility analytics on TimescaleDB + PostGIS + Uber H3. Spring Boot ingestion, Kafka stream processing, Server-Sent Events for live dashboards. Smart-city back-end blueprint.", + "10_desc": "Reference implementation of the BCBS 239 risk-data-aggregation lakehouse pattern on Databricks + Delta Lake + Unity Catalog + dbt-databricks. MIT-licensed, synthetic data only — banking risk-data engineering portfolio piece.", + "11_desc": "Serverless middleware enforcing responsible-AI compliance on LLM applications — PII detection, bias screening, hate-speech filtering, and RAG-powered policy enforcement on top of Azure OpenAI.", + "12_desc": "Cloud Carbon Intelligence platform estimating CO2e emissions from Azure infrastructure with AI-powered reduction recommendations. Clean Architecture, Azure AI Search semantic factor lookup, 88 automated tests. Built for EU CSRD Scope 3 compliance." }, "skills": { "label": "04 — SKILLS", diff --git a/src/messages/my.json b/src/messages/my.json index 9d91cf3..58da97a 100644 --- a/src/messages/my.json +++ b/src/messages/my.json @@ -14,7 +14,7 @@ "resume": "ကိုယ်ရေးအကျဉ်း" }, "hero": { - "subtitle": "FULL-STACK AI ENGINEER · STATION F · PARIS", + "subtitle": "တည်ထောင်သူ · FULL-STACK & AI အင်ဂျင်နီယာ · PARIS", "specialties": "AI Engineering · Full-Stack Systems · Backend & Cloud Data", "openTo": "OPEN TO AI / FULL-STACK / BACKEND ROLES · FR / DE / UK", "viewWork": "လုပ်ငန်းကြည့်ရန်", @@ -26,7 +26,7 @@ "heading": "AI Engineer · Full-Stack ·", "headingEm": "Backend Systems", "quote": "AI Engineer · Full-Stack · Backend Systems — building production-grade software at the intersection of telecom, healthcare, and finance, across Asia and Europe.", - "p1": "Currently a Full-Stack AI Engineer at Siloett.AI (Station F, Paris), where I architect end-to-end Generative AI systems on Azure with FastAPI, Azure Functions, and React/TypeScript.", + "p1": "လက်ရှိတွင် မြန်မာအတွက် EdTech တည်ဆောက်နေသော ကိုယ်ပိုင်ရင်းနှီးမြှုပ်နှံ software & AI studio ဖြစ်သည့် Ekkhara ၏ တည်ထောင်သူဖြစ်သည် — မကြာသေးမီက ထုတ်လုပ်ခဲ့သည့် SpeakProof သည် VPN မလိုဘဲ အသုံးပြုနိုင်သော Telegram-native TOEFL လေ့ကျင့်ရေး bot ဖြစ်သည်။ ယခင်က Siloett.AI (Station F, Paris) တွင် Full-Stack AI အင်ဂျင်နီယာအဖြစ် FastAPI နှင့် React/TypeScript သုံး၍ Azure ပေါ်တွင် end-to-end Generative AI စနစ်များ ဒီဇိုင်းဆွဲခဲ့သည်။", "p2": "Beyond AI, my engineering portfolio spans backend systems — Java 21, Spring Boot 3.5, Kafka, microservices — and cloud data engineering on AWS, Snowflake, Databricks, dbt, and Airflow. Telecom domain depth includes CDR pipelines, SMPP gateways, and Diameter Credit-Control.", "p3": "Dual Master's degrees from Telecom SudParis (Paris) and AIT (Bangkok), plus 5+ years shipping production software across healthcare, RegTech, telecom, and smart-city domains.", "p4": "Currently exploring AI Engineer, Full-Stack, and Backend Engineer roles across France, Germany, and the UK. If you're hiring or know of a fit — let's talk.", @@ -40,37 +40,43 @@ "label": "02 — EXPERIENCE", "heading": "တည်ဆောက်ခဲ့ပြီး", "headingEm": "သင်ယူခဲ့သည့်နေရာများ", - "0_job": "Full-Stack AI အင်ဂျင်နီယာ", - "0_badge": "AI Safety & Compliance · Station F · Paris", - "0_date": "Jun 2025 — May 2026", - "0_pt0": "အစမှအဆုံး Generative AI ပလက်ဖောင်းတစ်ခုကို ဗိသုကာပုံစံရေးဆွဲပြီး တည်ဆောက်ခဲ့သည် — LLM orchestration၊ RAG pipelines နှင့် Python (FastAPI) နှင့် Azure Functions serverless backend ပါဝင်သော production React/TypeScript frontend", - "0_pt1": "Content-safety filters၊ bias-detection checks နှင့် compliance guardrails များပါဝင်သော တာဝန်ယူမှုရှိသော AI validation layers များ ဒီဇိုင်းဆွဲပြီး အကောင်အထည်ဖော်ခဲ့ပြီး AI မှထုတ်လုပ်သော ရလဒ်အားလုံး စည်းမျဉ်းနှင့် ကျင့်ဝတ်စံနှုန်းများ ပြည့်မီကြောင်း သေချာစေခဲ့သည်", - "0_pt2": "Audit logging၊ provenance tracking နှင့် output attribution pipelines များပါဝင်သော AI safety နှင့် IP compliance စနစ်များ တည်ဆောက်ခဲ့ပြီး ခြေရာခံနိုင်ပြီး တာဝန်ခံနိုင်သော AI output lifecycle များ သေချာစေခဲ့သည်", - "0_pt3": "Azure OpenAI GPT-4o နှင့် LangChain အသုံးပြု၍ prompt-engineering နှင့် LLM evaluation frameworks များ ဖန်တီးခဲ့ပြီး compliance use cases များတွင် domain accuracy ကောင်းမွန်စေရန် စနစ်တကျ fine-tuning ပြုလုပ်ခဲ့သည်", - "1_job": "Data Science / Cloud Data Engineer", - "1_badge": "Station F · Paris", - "1_date": "Jul 2024 — Dec 2025", - "1_pt0": "မြို့ပြသွားလာမှု ခွဲခြမ်းစိတ်ဖြာရေးအတွက် Microsoft Azure Batch နှင့် Docker အသုံးပြု၍ cloud-based batch data processing pipeline ဒီဇိုင်းဆွဲခဲ့သည်", - "1_pt1": "Computer Vision နှင့် Bluetooth sensor workflows များကို အလိုအလျောက်လုပ်ဆောင်စေပြီး ချဲ့ထွင်နိုင်သော real-time smart city ထိုးထွင်းသိမြင်မှုများ ရရှိစေခဲ့သည်", - "1_pt2": "မြို့တော်အစိုးရနှင့် သယ်ယူပို့ဆောင်ရေး သက်ဆိုင်သူများ လက်ခံအသုံးပြုသော production analytics dashboards များ ပေးအပ်ခဲ့သည်", - "2_job": "သုတေသန & Back-End အင်ဂျင်နီယာ", - "2_badge": "Computer Vision · Backend AI", - "2_date": "Aug 2023 — Jul 2024", - "2_pt0": "Partner အဖွဲ့အစည်းများသို့ applied-AI စွမ်းရည်များ ပေးအပ်သော သုတေသနဓာတ်ခွဲခန်းတစ်ခုအတွက် back-end services နှင့် data pipelines များ တည်ဆောက်ခဲ့သည် — computer vision နှင့် NLP သုတေသနကို Python API များဖြင့် production သို့ ပြောင်းလဲခဲ့သည်", - "2_pt1": "ကိုယ်တိုင်ပြုစုထားသော gold-labeled WikiHow corpus ၁၀,၀၀၀ အပေါ်တွင် အင်္ဂလိပ်-မြန်မာ machine translation system တစ်ခုလုံး တည်ဆောက်ခဲ့သည် — dataset construction၊ model training၊ evaluation နှင့် public API deployment အထိ တာဝန်ယူခဲ့သည်", - "2_pt2": "Computer vision နှင့် multilingual NLP တွင် ဆန်းသစ်သော research prototype များနှင့် ၎င်းတို့ကို ဝန်ဆောင်ပေးရန် back-end infrastructure ကို တီထွင်ခဲ့သည် — ဓာတ်ခွဲခန်းသုတေသနကို ပြန်လည်အသုံးပြုနိုင်ပြီး deploy လုပ်နိုင်သော tools အဖြစ် ပြောင်းလဲခဲ့သည်", + "0_job": "တည်ထောင်သူ & Full-Stack / AI အင်ဂျင်နီယာ", + "0_badge": "တည်ထောင်သူ · မြန်မာအတွက် EdTech", + "0_date": "May 2026 — Present", + "0_pt0": "ကိုယ်ပိုင်ရင်းနှီးမြှုပ်နှံထားသော software & AI studio ဖြစ်သည့် Ekkhara ကို တည်ထောင်ခဲ့ပြီး မြန်မာအတွက် EdTech ထုတ်ကုန်များ တည်ဆောက်နေသည် — ထုတ်ကုန်တစ်ခုစီကို စိတ်ကူးမှ အသုံးပြုနိုင်သည်အထိ ဦးဆောင်ကာ architecture၊ backend၊ AI နှင့် front-end ကို အစအဆုံး တာဝန်ယူသည်။", + "0_pt1": "Telegram အတွင်း၌ပင် အပြည့်အဝအလုပ်လုပ်သော TOEFL speaking နှင့် အင်္ဂလိပ်လေ့ကျင့်ရေး bot ဖြစ်သည့် SpeakProof ကို တည်ဆောက်ခဲ့သည် — မြန်မာနိုင်ငံ၏ အင်တာနက်ကန့်သတ်ချက်များကြားမှ VPN မလိုဘဲ၊ နေ့စဉ်သုံးနေကျ app မှတစ်ဆင့် TOEFL (computer-based test) အတွက် လေ့ကျင့်နိုင်စေသည်။", + "0_pt2": "ထုတ်ကုန်တစ်ခုစီ၏ နောက်ကွယ်ရှိ full stack ကို တည်ဆောက်သည် — Python / FastAPI services၊ LLM ဖြင့်မောင်းနှင်သော feedback နှင့် scoring၊ နှင့် conversational UX — access နှင့် infrastructure ကန့်သတ်ထားသည့်နေရာများရှိ အသုံးပြုသူများထံ ရောက်ရှိစေသော AI tools များ ပေးပို့သည်။", + "1_job": "Full-Stack AI အင်ဂျင်နီယာ", + "1_badge": "AI Safety & Compliance · Station F · Paris", + "1_date": "Jun 2025 — May 2026", + "1_pt0": "အစမှအဆုံး Generative AI ပလက်ဖောင်းတစ်ခုကို ဗိသုကာပုံစံရေးဆွဲပြီး တည်ဆောက်ခဲ့သည် — LLM orchestration၊ RAG pipelines နှင့် Python (FastAPI) နှင့် Azure Functions serverless backend ပါဝင်သော production React/TypeScript frontend", + "1_pt1": "Content-safety filters၊ bias-detection checks နှင့် compliance guardrails များပါဝင်သော တာဝန်ယူမှုရှိသော AI validation layers များ ဒီဇိုင်းဆွဲပြီး အကောင်အထည်ဖော်ခဲ့ပြီး AI မှထုတ်လုပ်သော ရလဒ်အားလုံး စည်းမျဉ်းနှင့် ကျင့်ဝတ်စံနှုန်းများ ပြည့်မီကြောင်း သေချာစေခဲ့သည်", + "1_pt2": "Audit logging၊ provenance tracking နှင့် output attribution pipelines များပါဝင်သော AI safety နှင့် IP compliance စနစ်များ တည်ဆောက်ခဲ့ပြီး ခြေရာခံနိုင်ပြီး တာဝန်ခံနိုင်သော AI output lifecycle များ သေချာစေခဲ့သည်", + "1_pt3": "Azure OpenAI GPT-4o နှင့် LangChain အသုံးပြု၍ prompt-engineering နှင့် LLM evaluation frameworks များ ဖန်တီးခဲ့ပြီး compliance use cases များတွင် domain accuracy ကောင်းမွန်စေရန် စနစ်တကျ fine-tuning ပြုလုပ်ခဲ့သည်", + "2_job": "Data Science / Cloud Data Engineer", + "2_badge": "Station F · Paris", + "2_date": "Jul 2024 — Dec 2025", + "2_pt0": "မြို့ပြသွားလာမှု ခွဲခြမ်းစိတ်ဖြာရေးအတွက် Microsoft Azure Batch နှင့် Docker အသုံးပြု၍ cloud-based batch data processing pipeline ဒီဇိုင်းဆွဲခဲ့သည်", + "2_pt1": "Computer Vision နှင့် Bluetooth sensor workflows များကို အလိုအလျောက်လုပ်ဆောင်စေပြီး ချဲ့ထွင်နိုင်သော real-time smart city ထိုးထွင်းသိမြင်မှုများ ရရှိစေခဲ့သည်", + "2_pt2": "မြို့တော်အစိုးရနှင့် သယ်ယူပို့ဆောင်ရေး သက်ဆိုင်သူများ လက်ခံအသုံးပြုသော production analytics dashboards များ ပေးအပ်ခဲ့သည်", "3_job": "သုတေသန & Back-End အင်ဂျင်နီယာ", - "3_badge": "Applied-AI Lab · Backend", - "3_date": "Jan 2023 — Aug 2023", - "3_pt0": "ကုမ္ပဏီများသို့ applied-AI ဝန်ဆောင်မှုများ ပေးအပ်သော သုတေသနဓာတ်ခွဲခန်းတစ်ခုတွင် NLP paraphrasing tool တစ်ခုကို model မှ back-end API အထိ အစအဆုံး တည်ဆောက်ခဲ့သည်", - "3_pt1": "Data layer ကို တည်ဆောက်ခဲ့သည် — training datasets များကို သန့်ရှင်းရေးနှင့် ဖွဲ့စည်းခြင်း — ပြီး training workflows များ ပိုမိုကောင်းမွန်စေကာ model accuracy ကို ၁၅% တိုးမြှင့်ခဲ့သည်", - "3_pt2": "ဓာတ်ခွဲခန်း၏ AI tools များအတွက် back-end operations ကို တာဝန်ယူခဲ့ပြီး data management နှင့် R&D engineering အလေ့အကျင့်များ အားကောင်းစေခဲ့သည်", - "4_job": "ဆော့ဖ်ဝဲ အင်ဂျင်နီယာ (Web)", - "4_badge": "Full-Stack Web · UN အေဂျင်စီ", - "4_date": "Jan 2021 — Dec 2022", - "4_pt0": "ကုလသမဂ္ဂအေဂျင်စီ (FAO) အတွက် full-stack web applications များ တည်ဆောက်ခဲ့သည် — စိုက်ပျိုးရေးနှင့် စားနပ်ရိက္ခာဖူလုံရေး program data များကို ဝန်ထမ်းများနှင့် ကွင်းဆင်းအဖွဲ့များထံ ပေးပို့သည့် internal data dashboards နှင့် အများသုံး portals များ ဖန်တီးခဲ့သည်", - "4_pt1": "ကွင်းဆင်း data ကောက်ယူရေး tools များနှင့် ၎င်းတို့၏နောက်ကွယ်ရှိ back-end APIs များ ဒီဇိုင်းဆွဲခဲ့ပြီး၊ ကွင်းဆင်းအရာရှိများသည် program data များကို ကောက်ယူ၊ စိစစ်ပြီး ဗဟို reporting systems များသို့ sync လုပ်နိုင်စေခဲ့သည်", - "4_pt2": "stack တစ်ခုလုံးတွင် features များကို end-to-end တာဝန်ယူခဲ့သည် — React/Next.js + TypeScript front-ends နှင့် Python နှင့် PHP/CMS back-ends — data model နှင့် REST API မှ deploy လုပ်ပြီးသား UI အထိ" + "3_badge": "Computer Vision · Backend AI", + "3_date": "Aug 2023 — Jul 2024", + "3_pt0": "Partner အဖွဲ့အစည်းများသို့ applied-AI စွမ်းရည်များ ပေးအပ်သော သုတေသနဓာတ်ခွဲခန်းတစ်ခုအတွက် back-end services နှင့် data pipelines များ တည်ဆောက်ခဲ့သည် — computer vision နှင့် NLP သုတေသနကို Python API များဖြင့် production သို့ ပြောင်းလဲခဲ့သည်", + "3_pt1": "ကိုယ်တိုင်ပြုစုထားသော gold-labeled WikiHow corpus ၁၀,၀၀၀ အပေါ်တွင် အင်္ဂလိပ်-မြန်မာ machine translation system တစ်ခုလုံး တည်ဆောက်ခဲ့သည် — dataset construction၊ model training၊ evaluation နှင့် public API deployment အထိ တာဝန်ယူခဲ့သည်", + "3_pt2": "Computer vision နှင့် multilingual NLP တွင် ဆန်းသစ်သော research prototype များနှင့် ၎င်းတို့ကို ဝန်ဆောင်ပေးရန် back-end infrastructure ကို တီထွင်ခဲ့သည် — ဓာတ်ခွဲခန်းသုတေသနကို ပြန်လည်အသုံးပြုနိုင်ပြီး deploy လုပ်နိုင်သော tools အဖြစ် ပြောင်းလဲခဲ့သည်", + "4_job": "သုတေသန & Back-End အင်ဂျင်နီယာ", + "4_badge": "Applied-AI Lab · Backend", + "4_date": "Jan 2023 — Aug 2023", + "4_pt0": "ကုမ္ပဏီများသို့ applied-AI ဝန်ဆောင်မှုများ ပေးအပ်သော သုတေသနဓာတ်ခွဲခန်းတစ်ခုတွင် NLP paraphrasing tool တစ်ခုကို model မှ back-end API အထိ အစအဆုံး တည်ဆောက်ခဲ့သည်", + "4_pt1": "Data layer ကို တည်ဆောက်ခဲ့သည် — training datasets များကို သန့်ရှင်းရေးနှင့် ဖွဲ့စည်းခြင်း — ပြီး training workflows များ ပိုမိုကောင်းမွန်စေကာ model accuracy ကို ၁၅% တိုးမြှင့်ခဲ့သည်", + "4_pt2": "ဓာတ်ခွဲခန်း၏ AI tools များအတွက် back-end operations ကို တာဝန်ယူခဲ့ပြီး data management နှင့် R&D engineering အလေ့အကျင့်များ အားကောင်းစေခဲ့သည်", + "5_job": "ဆော့ဖ်ဝဲ အင်ဂျင်နီယာ (Web)", + "5_badge": "Full-Stack Web · UN အေဂျင်စီ", + "5_date": "Jan 2021 — Dec 2022", + "5_pt0": "ကုလသမဂ္ဂအေဂျင်စီ (FAO) အတွက် full-stack web applications များ တည်ဆောက်ခဲ့သည် — စိုက်ပျိုးရေးနှင့် စားနပ်ရိက္ခာဖူလုံရေး program data များကို ဝန်ထမ်းများနှင့် ကွင်းဆင်းအဖွဲ့များထံ ပေးပို့သည့် internal data dashboards နှင့် အများသုံး portals များ ဖန်တီးခဲ့သည်", + "5_pt1": "ကွင်းဆင်း data ကောက်ယူရေး tools များနှင့် ၎င်းတို့၏နောက်ကွယ်ရှိ back-end APIs များ ဒီဇိုင်းဆွဲခဲ့ပြီး၊ ကွင်းဆင်းအရာရှိများသည် program data များကို ကောက်ယူ၊ စိစစ်ပြီး ဗဟို reporting systems များသို့ sync လုပ်နိုင်စေခဲ့သည်", + "5_pt2": "stack တစ်ခုလုံးတွင် features များကို end-to-end တာဝန်ယူခဲ့သည် — React/Next.js + TypeScript front-ends နှင့် Python နှင့် PHP/CMS back-ends — data model နှင့် REST API မှ deploy လုပ်ပြီးသား UI အထိ" }, "projects": { "label": "03 — PROJECTS", @@ -83,19 +89,21 @@ "demo": "သရုပ်ပြ", "gh": "GH", "liveAtVercel": "LIVE ON VERCEL", + "liveAtTelegram": "LIVE ON TELEGRAM", "openSourceOnGithub": "OPEN-SOURCE ON GITHUB", - "0_desc": "Real-time European grid lakehouse on AWS — probabilistic load forecasting (DeepAR / quantile loss) and stochastic optimisation for battery flexibility decisions. Medallion architecture on S3 + Iceberg, MSK Kafka streaming, dbt models, Airflow orchestration, MLflow tracking. Cloud Data Engineering portfolio piece.", - "1_desc": "Event-driven Call Detail Record ingestion, rating, and reconciliation pipeline simulating an MVNO billing back-end. Idempotent Kafka consumers, Spring Boot 3.5 microservices, MySQL for rated CDRs, MongoDB for raw events, Docker Compose for local infra. Built around real telecom domain models (3GPP TS 32.298).", - "2_desc": "End-to-end CSRD/ESRS sustainability data pipeline — Claude/Mistral GenAI extraction from sustainability reports with page-level audit lineage, Snowflake warehouse (validated) + DuckDB local dev, dbt transformations, Airflow orchestration. Built for EU corporate sustainability reporting compliance.", - "3_desc": "AI-powered blood test interpretation for personalised supplement guidance — competing at Haleon VivaTech 2026. OCR ingestion of French lab reports, validated biomarker classification, longitudinal tracking, and supplement recommendations grounded in clinical evidence. Real-data moat through partner lab integrations.", - "4_desc": "From-scratch ReAct Agent Observatory — observe, debug, and benchmark LLM agents with a built-in 8-type failure taxonomy (hallucinated tools, malformed actions, context overflow, goal drift, …) and multi-provider eval harness (Groq, OpenAI, Anthropic, Google, Ollama). Composite scoring (answer + tools + efficiency + reliability), Clean Architecture FastAPI + PostgreSQL backend, Next.js 16 frontend with real-time SSE streaming. 50+ benchmark cases, 81 tests.", - "5_desc": "Real-World Evidence platform for vaccine research — full-stack application for ingesting, analyzing, and visualizing vaccine safety and efficacy data from real-world sources at scale. Built at Siloett.AI for healthcare and life-sciences buyers.", - "6_desc": "Diameter Credit-Control Server (Gy / RFC 4006 / App-Id 4) for real-time prepaid mobile billing. Idempotent partial debits, jdiameter 1.7.x stack, designed against TRANSATEL/MVNO production patterns.", - "7_desc": "Java SMPP v3.4 gateway bridging inbound SMS (submit_sm) to RabbitMQ for downstream processing. Spring Boot 3.5 + jsmpp 3.0, dockerised, designed for MVNO and telecom messaging platforms.", - "8_desc": "Real-time urban mobility analytics on TimescaleDB + PostGIS + Uber H3. Spring Boot ingestion, Kafka stream processing, Server-Sent Events for live dashboards. Smart-city back-end blueprint.", - "9_desc": "Reference implementation of the BCBS 239 risk-data-aggregation lakehouse pattern on Databricks + Delta Lake + Unity Catalog + dbt-databricks. MIT-licensed, synthetic data only — banking risk-data engineering portfolio piece.", - "10_desc": "Serverless middleware enforcing responsible-AI compliance on LLM applications — PII detection, bias screening, hate-speech filtering, and RAG-powered policy enforcement on top of Azure OpenAI.", - "11_desc": "Cloud Carbon Intelligence platform estimating CO2e emissions from Azure infrastructure with AI-powered reduction recommendations. Clean Architecture, Azure AI Search semantic factor lookup, 88 automated tests. Built for EU CSRD Scope 3 compliance." + "0_desc": "Telegram-native TOEFL speaking & English-practice bot for Myanmar learners — drill toward the TOEFL computer-based test inside an app people already use daily, with zero VPN needed despite nationwide internet restrictions. LLM-powered speaking feedback and scoring on a Python / FastAPI backend. An Ekkhara EdTech product.", + "1_desc": "Real-time European grid lakehouse on AWS — probabilistic load forecasting (DeepAR / quantile loss) and stochastic optimisation for battery flexibility decisions. Medallion architecture on S3 + Iceberg, MSK Kafka streaming, dbt models, Airflow orchestration, MLflow tracking. Cloud Data Engineering portfolio piece.", + "2_desc": "Event-driven Call Detail Record ingestion, rating, and reconciliation pipeline simulating an MVNO billing back-end. Idempotent Kafka consumers, Spring Boot 3.5 microservices, MySQL for rated CDRs, MongoDB for raw events, Docker Compose for local infra. Built around real telecom domain models (3GPP TS 32.298).", + "3_desc": "End-to-end CSRD/ESRS sustainability data pipeline — Claude/Mistral GenAI extraction from sustainability reports with page-level audit lineage, Snowflake warehouse (validated) + DuckDB local dev, dbt transformations, Airflow orchestration. Built for EU corporate sustainability reporting compliance.", + "4_desc": "AI-powered blood test interpretation for personalised supplement guidance — competing at Haleon VivaTech 2026. OCR ingestion of French lab reports, validated biomarker classification, longitudinal tracking, and supplement recommendations grounded in clinical evidence. Real-data moat through partner lab integrations.", + "5_desc": "From-scratch ReAct Agent Observatory — observe, debug, and benchmark LLM agents with a built-in 8-type failure taxonomy (hallucinated tools, malformed actions, context overflow, goal drift, …) and multi-provider eval harness (Groq, OpenAI, Anthropic, Google, Ollama). Composite scoring (answer + tools + efficiency + reliability), Clean Architecture FastAPI + PostgreSQL backend, Next.js 16 frontend with real-time SSE streaming. 50+ benchmark cases, 81 tests.", + "6_desc": "Real-World Evidence platform for vaccine research — full-stack application for ingesting, analyzing, and visualizing vaccine safety and efficacy data from real-world sources at scale. Built at Siloett.AI for healthcare and life-sciences buyers.", + "7_desc": "Diameter Credit-Control Server (Gy / RFC 4006 / App-Id 4) for real-time prepaid mobile billing. Idempotent partial debits, jdiameter 1.7.x stack, designed against TRANSATEL/MVNO production patterns.", + "8_desc": "Java SMPP v3.4 gateway bridging inbound SMS (submit_sm) to RabbitMQ for downstream processing. Spring Boot 3.5 + jsmpp 3.0, dockerised, designed for MVNO and telecom messaging platforms.", + "9_desc": "Real-time urban mobility analytics on TimescaleDB + PostGIS + Uber H3. Spring Boot ingestion, Kafka stream processing, Server-Sent Events for live dashboards. Smart-city back-end blueprint.", + "10_desc": "Reference implementation of the BCBS 239 risk-data-aggregation lakehouse pattern on Databricks + Delta Lake + Unity Catalog + dbt-databricks. MIT-licensed, synthetic data only — banking risk-data engineering portfolio piece.", + "11_desc": "Serverless middleware enforcing responsible-AI compliance on LLM applications — PII detection, bias screening, hate-speech filtering, and RAG-powered policy enforcement on top of Azure OpenAI.", + "12_desc": "Cloud Carbon Intelligence platform estimating CO2e emissions from Azure infrastructure with AI-powered reduction recommendations. Clean Architecture, Azure AI Search semantic factor lookup, 88 automated tests. Built for EU CSRD Scope 3 compliance." }, "skills": { "label": "04 — SKILLS", diff --git a/src/messages/pt.json b/src/messages/pt.json index 9605132..d0a0214 100644 --- a/src/messages/pt.json +++ b/src/messages/pt.json @@ -14,7 +14,7 @@ "resume": "CURRÍCULO" }, "hero": { - "subtitle": "FULL-STACK AI ENGINEER · STATION F · PARIS", + "subtitle": "FUNDADOR · ENGENHEIRO FULL-STACK & IA · PARIS", "specialties": "AI Engineering · Full-Stack Systems · Backend & Cloud Data", "openTo": "OPEN TO AI / FULL-STACK / BACKEND ROLES · FR / DE / UK", "viewWork": "VER TRABALHOS", @@ -26,7 +26,7 @@ "heading": "AI Engineer · Full-Stack ·", "headingEm": "Backend Systems", "quote": "AI Engineer · Full-Stack · Backend Systems — building production-grade software at the intersection of telecom, healthcare, and finance, across Asia and Europe.", - "p1": "Currently a Full-Stack AI Engineer at Siloett.AI (Station F, Paris), where I architect end-to-end Generative AI systems on Azure with FastAPI, Azure Functions, and React/TypeScript.", + "p1": "Atualmente fundador da Ekkhara, um estúdio de software e IA autofinanciado que cria EdTech para Mianmar — mais recentemente o SpeakProof, um bot de prática de TOEFL nativo do Telegram que funciona sem VPN. Antes, fui Engenheiro Full-Stack de IA na Siloett.AI (Station F, Paris), projetando sistemas de IA generativa de ponta a ponta no Azure com FastAPI e React/TypeScript.", "p2": "Beyond AI, my engineering portfolio spans backend systems — Java 21, Spring Boot 3.5, Kafka, microservices — and cloud data engineering on AWS, Snowflake, Databricks, dbt, and Airflow. Telecom domain depth includes CDR pipelines, SMPP gateways, and Diameter Credit-Control.", "p3": "Dual Master's degrees from Telecom SudParis (Paris) and AIT (Bangkok), plus 5+ years shipping production software across healthcare, RegTech, telecom, and smart-city domains.", "p4": "Currently exploring AI Engineer, Full-Stack, and Backend Engineer roles across France, Germany, and the UK. If you're hiring or know of a fit — let's talk.", @@ -40,37 +40,43 @@ "label": "02 — EXPERIENCE", "heading": "Onde eu", "headingEm": "Construí & Aprendi", - "0_job": "Engenheiro de IA Full-Stack", - "0_badge": "AI Safety & Compliance · Station F · Paris", - "0_date": "Jun 2025 — May 2026", - "0_pt0": "Arquitetei e construí uma plataforma de IA Generativa ponta a ponta do zero — orquestração de LLM, pipelines RAG e um frontend de produção em React/TypeScript com backend serverless em Python (FastAPI) e Azure Functions", - "0_pt1": "Projetei e implementei camadas de validação de IA responsável incluindo filtros de segurança de conteúdo, verificações de detecção de viés e guardrails de conformidade garantindo que todas as saídas geradas por IA atendam aos padrões regulatórios e éticos", - "0_pt2": "Construí sistemas de segurança de IA e conformidade de PI incluindo registro de auditoria, rastreamento de proveniência e pipelines de atribuição de saída — garantindo ciclos de vida de saída de IA rastreáveis e responsáveis", - "0_pt3": "Desenvolvi frameworks de prompt engineering e avaliação de LLM usando Azure OpenAI GPT-4o e LangChain, com ajuste fino sistemático para otimizar a precisão de domínio em casos de uso de conformidade", - "1_job": "Ciência de Dados / Engenheiro de Dados Cloud", - "1_badge": "Station F · Paris", - "1_date": "Jul 2024 — Dec 2025", - "1_pt0": "Projetei um pipeline de processamento de dados em lote baseado em nuvem usando Microsoft Azure Batch e Docker para análise de mobilidade urbana", - "1_pt1": "Automatizei fluxos de trabalho de Visão Computacional e sensores Bluetooth permitindo insights de cidade inteligente escaláveis e em tempo real", - "1_pt2": "Entreguei dashboards de análise em produção adotados por governos municipais e partes interessadas do setor de transporte", - "2_job": "Engenheiro de Pesquisa e Back-End", - "2_badge": "Visão Computacional · IA Backend", - "2_date": "Aug 2023 — Jul 2024", - "2_pt0": "Desenvolvi serviços back-end e pipelines de dados para um laboratório de pesquisa que entrega capacidades de IA aplicada a organizações parceiras — levando pesquisa de visão computacional e NLP para produção atrás de APIs em Python", - "2_pt1": "Construí um sistema completo de tradução automática inglês–birmanês sobre um corpus WikiHow de 10K amostras rotuladas manualmente — da construção do dataset ao treinamento, avaliação e implantação atrás de uma API pública", - "2_pt2": "Desenvolvi protótipos de pesquisa inovadores em visão computacional e NLP multilíngue, além da infraestrutura back-end para servi-los — transformando a pesquisa do laboratório em ferramentas reproduzíveis e implantáveis", + "0_job": "Fundador & Engenheiro Full-Stack / IA", + "0_badge": "Fundador · EdTech para Mianmar", + "0_date": "May 2026 — Present", + "0_pt0": "Fundei a Ekkhara, um estúdio de software e IA autofinanciado que cria produtos EdTech para Mianmar — levando cada um da ideia ao produto no ar e dominando a arquitetura, o backend, a IA e o frontend de ponta a ponta.", + "0_pt1": "Criei o SpeakProof, um bot de speaking do TOEFL e prática de inglês que funciona inteiramente dentro do Telegram — permitindo que estudantes de Mianmar treinem para o TOEFL (prova por computador) a partir de um app que já usam diariamente, sem precisar de VPN apesar das restrições de internet do país.", + "0_pt2": "Desenvolvo toda a stack por trás de cada produto — serviços Python / FastAPI, feedback e pontuação guiados por LLM e UX conversacional — entregando ferramentas de IA que alcançam usuários onde o acesso e a infraestrutura são limitados.", + "1_job": "Engenheiro de IA Full-Stack", + "1_badge": "AI Safety & Compliance · Station F · Paris", + "1_date": "Jun 2025 — May 2026", + "1_pt0": "Arquitetei e construí uma plataforma de IA Generativa ponta a ponta do zero — orquestração de LLM, pipelines RAG e um frontend de produção em React/TypeScript com backend serverless em Python (FastAPI) e Azure Functions", + "1_pt1": "Projetei e implementei camadas de validação de IA responsável incluindo filtros de segurança de conteúdo, verificações de detecção de viés e guardrails de conformidade garantindo que todas as saídas geradas por IA atendam aos padrões regulatórios e éticos", + "1_pt2": "Construí sistemas de segurança de IA e conformidade de PI incluindo registro de auditoria, rastreamento de proveniência e pipelines de atribuição de saída — garantindo ciclos de vida de saída de IA rastreáveis e responsáveis", + "1_pt3": "Desenvolvi frameworks de prompt engineering e avaliação de LLM usando Azure OpenAI GPT-4o e LangChain, com ajuste fino sistemático para otimizar a precisão de domínio em casos de uso de conformidade", + "2_job": "Ciência de Dados / Engenheiro de Dados Cloud", + "2_badge": "Station F · Paris", + "2_date": "Jul 2024 — Dec 2025", + "2_pt0": "Projetei um pipeline de processamento de dados em lote baseado em nuvem usando Microsoft Azure Batch e Docker para análise de mobilidade urbana", + "2_pt1": "Automatizei fluxos de trabalho de Visão Computacional e sensores Bluetooth permitindo insights de cidade inteligente escaláveis e em tempo real", + "2_pt2": "Entreguei dashboards de análise em produção adotados por governos municipais e partes interessadas do setor de transporte", "3_job": "Engenheiro de Pesquisa e Back-End", - "3_badge": "Laboratório de IA Aplicada · Backend", - "3_date": "Jan 2023 — Aug 2023", - "3_pt0": "Construí de ponta a ponta uma ferramenta de paráfrase com NLP em um laboratório de pesquisa que oferece serviços de IA aplicada a empresas — do modelo à API back-end", - "3_pt1": "Projetei a camada de dados — limpeza e estruturação de datasets de treinamento — e otimizei os fluxos de treinamento, melhorando a precisão do modelo em 15%", - "3_pt2": "Responsável pelas operações back-end das ferramentas de IA do laboratório, fortalecendo o gerenciamento de dados e a prática de engenharia de P&D", - "4_job": "Engenheiro de Software (Web)", - "4_badge": "Full-Stack Web · Agência da ONU", - "4_date": "Jan 2021 — Dec 2022", - "4_pt0": "Desenvolvi aplicações web full-stack para uma agência da ONU (FAO) — painéis de dados internos e portais públicos que entregavam dados de programas de agricultura e segurança alimentar à equipe e aos times de campo", - "4_pt1": "Projetei ferramentas de coleta de dados em campo e as APIs back-end por trás delas, permitindo que os agentes de campo capturassem, validassem e sincronizassem dados de programas em sistemas centralizados de relatórios", - "4_pt2": "Responsável por funcionalidades de ponta a ponta em toda a stack — front-ends em React/Next.js + TypeScript com back-ends em Python e PHP/CMS — do modelo de dados e da REST API até a UI implantada" + "3_badge": "Visão Computacional · IA Backend", + "3_date": "Aug 2023 — Jul 2024", + "3_pt0": "Desenvolvi serviços back-end e pipelines de dados para um laboratório de pesquisa que entrega capacidades de IA aplicada a organizações parceiras — levando pesquisa de visão computacional e NLP para produção atrás de APIs em Python", + "3_pt1": "Construí um sistema completo de tradução automática inglês–birmanês sobre um corpus WikiHow de 10K amostras rotuladas manualmente — da construção do dataset ao treinamento, avaliação e implantação atrás de uma API pública", + "3_pt2": "Desenvolvi protótipos de pesquisa inovadores em visão computacional e NLP multilíngue, além da infraestrutura back-end para servi-los — transformando a pesquisa do laboratório em ferramentas reproduzíveis e implantáveis", + "4_job": "Engenheiro de Pesquisa e Back-End", + "4_badge": "Laboratório de IA Aplicada · Backend", + "4_date": "Jan 2023 — Aug 2023", + "4_pt0": "Construí de ponta a ponta uma ferramenta de paráfrase com NLP em um laboratório de pesquisa que oferece serviços de IA aplicada a empresas — do modelo à API back-end", + "4_pt1": "Projetei a camada de dados — limpeza e estruturação de datasets de treinamento — e otimizei os fluxos de treinamento, melhorando a precisão do modelo em 15%", + "4_pt2": "Responsável pelas operações back-end das ferramentas de IA do laboratório, fortalecendo o gerenciamento de dados e a prática de engenharia de P&D", + "5_job": "Engenheiro de Software (Web)", + "5_badge": "Full-Stack Web · Agência da ONU", + "5_date": "Jan 2021 — Dec 2022", + "5_pt0": "Desenvolvi aplicações web full-stack para uma agência da ONU (FAO) — painéis de dados internos e portais públicos que entregavam dados de programas de agricultura e segurança alimentar à equipe e aos times de campo", + "5_pt1": "Projetei ferramentas de coleta de dados em campo e as APIs back-end por trás delas, permitindo que os agentes de campo capturassem, validassem e sincronizassem dados de programas em sistemas centralizados de relatórios", + "5_pt2": "Responsável por funcionalidades de ponta a ponta em toda a stack — front-ends em React/Next.js + TypeScript com back-ends em Python e PHP/CMS — do modelo de dados e da REST API até a UI implantada" }, "projects": { "label": "03 — PROJECTS", @@ -83,19 +89,21 @@ "demo": "DEMO", "gh": "GH", "liveAtVercel": "LIVE ON VERCEL", + "liveAtTelegram": "LIVE ON TELEGRAM", "openSourceOnGithub": "OPEN-SOURCE ON GITHUB", - "0_desc": "Real-time European grid lakehouse on AWS — probabilistic load forecasting (DeepAR / quantile loss) and stochastic optimisation for battery flexibility decisions. Medallion architecture on S3 + Iceberg, MSK Kafka streaming, dbt models, Airflow orchestration, MLflow tracking. Cloud Data Engineering portfolio piece.", - "1_desc": "Event-driven Call Detail Record ingestion, rating, and reconciliation pipeline simulating an MVNO billing back-end. Idempotent Kafka consumers, Spring Boot 3.5 microservices, MySQL for rated CDRs, MongoDB for raw events, Docker Compose for local infra. Built around real telecom domain models (3GPP TS 32.298).", - "2_desc": "End-to-end CSRD/ESRS sustainability data pipeline — Claude/Mistral GenAI extraction from sustainability reports with page-level audit lineage, Snowflake warehouse (validated) + DuckDB local dev, dbt transformations, Airflow orchestration. Built for EU corporate sustainability reporting compliance.", - "3_desc": "AI-powered blood test interpretation for personalised supplement guidance — competing at Haleon VivaTech 2026. OCR ingestion of French lab reports, validated biomarker classification, longitudinal tracking, and supplement recommendations grounded in clinical evidence. Real-data moat through partner lab integrations.", - "4_desc": "From-scratch ReAct Agent Observatory — observe, debug, and benchmark LLM agents with a built-in 8-type failure taxonomy (hallucinated tools, malformed actions, context overflow, goal drift, …) and multi-provider eval harness (Groq, OpenAI, Anthropic, Google, Ollama). Composite scoring (answer + tools + efficiency + reliability), Clean Architecture FastAPI + PostgreSQL backend, Next.js 16 frontend with real-time SSE streaming. 50+ benchmark cases, 81 tests.", - "5_desc": "Real-World Evidence platform for vaccine research — full-stack application for ingesting, analyzing, and visualizing vaccine safety and efficacy data from real-world sources at scale. Built at Siloett.AI for healthcare and life-sciences buyers.", - "6_desc": "Diameter Credit-Control Server (Gy / RFC 4006 / App-Id 4) for real-time prepaid mobile billing. Idempotent partial debits, jdiameter 1.7.x stack, designed against TRANSATEL/MVNO production patterns.", - "7_desc": "Java SMPP v3.4 gateway bridging inbound SMS (submit_sm) to RabbitMQ for downstream processing. Spring Boot 3.5 + jsmpp 3.0, dockerised, designed for MVNO and telecom messaging platforms.", - "8_desc": "Real-time urban mobility analytics on TimescaleDB + PostGIS + Uber H3. Spring Boot ingestion, Kafka stream processing, Server-Sent Events for live dashboards. Smart-city back-end blueprint.", - "9_desc": "Reference implementation of the BCBS 239 risk-data-aggregation lakehouse pattern on Databricks + Delta Lake + Unity Catalog + dbt-databricks. MIT-licensed, synthetic data only — banking risk-data engineering portfolio piece.", - "10_desc": "Serverless middleware enforcing responsible-AI compliance on LLM applications — PII detection, bias screening, hate-speech filtering, and RAG-powered policy enforcement on top of Azure OpenAI.", - "11_desc": "Cloud Carbon Intelligence platform estimating CO2e emissions from Azure infrastructure with AI-powered reduction recommendations. Clean Architecture, Azure AI Search semantic factor lookup, 88 automated tests. Built for EU CSRD Scope 3 compliance." + "0_desc": "Telegram-native TOEFL speaking & English-practice bot for Myanmar learners — drill toward the TOEFL computer-based test inside an app people already use daily, with zero VPN needed despite nationwide internet restrictions. LLM-powered speaking feedback and scoring on a Python / FastAPI backend. An Ekkhara EdTech product.", + "1_desc": "Real-time European grid lakehouse on AWS — probabilistic load forecasting (DeepAR / quantile loss) and stochastic optimisation for battery flexibility decisions. Medallion architecture on S3 + Iceberg, MSK Kafka streaming, dbt models, Airflow orchestration, MLflow tracking. Cloud Data Engineering portfolio piece.", + "2_desc": "Event-driven Call Detail Record ingestion, rating, and reconciliation pipeline simulating an MVNO billing back-end. Idempotent Kafka consumers, Spring Boot 3.5 microservices, MySQL for rated CDRs, MongoDB for raw events, Docker Compose for local infra. Built around real telecom domain models (3GPP TS 32.298).", + "3_desc": "End-to-end CSRD/ESRS sustainability data pipeline — Claude/Mistral GenAI extraction from sustainability reports with page-level audit lineage, Snowflake warehouse (validated) + DuckDB local dev, dbt transformations, Airflow orchestration. Built for EU corporate sustainability reporting compliance.", + "4_desc": "AI-powered blood test interpretation for personalised supplement guidance — competing at Haleon VivaTech 2026. OCR ingestion of French lab reports, validated biomarker classification, longitudinal tracking, and supplement recommendations grounded in clinical evidence. Real-data moat through partner lab integrations.", + "5_desc": "From-scratch ReAct Agent Observatory — observe, debug, and benchmark LLM agents with a built-in 8-type failure taxonomy (hallucinated tools, malformed actions, context overflow, goal drift, …) and multi-provider eval harness (Groq, OpenAI, Anthropic, Google, Ollama). Composite scoring (answer + tools + efficiency + reliability), Clean Architecture FastAPI + PostgreSQL backend, Next.js 16 frontend with real-time SSE streaming. 50+ benchmark cases, 81 tests.", + "6_desc": "Real-World Evidence platform for vaccine research — full-stack application for ingesting, analyzing, and visualizing vaccine safety and efficacy data from real-world sources at scale. Built at Siloett.AI for healthcare and life-sciences buyers.", + "7_desc": "Diameter Credit-Control Server (Gy / RFC 4006 / App-Id 4) for real-time prepaid mobile billing. Idempotent partial debits, jdiameter 1.7.x stack, designed against TRANSATEL/MVNO production patterns.", + "8_desc": "Java SMPP v3.4 gateway bridging inbound SMS (submit_sm) to RabbitMQ for downstream processing. Spring Boot 3.5 + jsmpp 3.0, dockerised, designed for MVNO and telecom messaging platforms.", + "9_desc": "Real-time urban mobility analytics on TimescaleDB + PostGIS + Uber H3. Spring Boot ingestion, Kafka stream processing, Server-Sent Events for live dashboards. Smart-city back-end blueprint.", + "10_desc": "Reference implementation of the BCBS 239 risk-data-aggregation lakehouse pattern on Databricks + Delta Lake + Unity Catalog + dbt-databricks. MIT-licensed, synthetic data only — banking risk-data engineering portfolio piece.", + "11_desc": "Serverless middleware enforcing responsible-AI compliance on LLM applications — PII detection, bias screening, hate-speech filtering, and RAG-powered policy enforcement on top of Azure OpenAI.", + "12_desc": "Cloud Carbon Intelligence platform estimating CO2e emissions from Azure infrastructure with AI-powered reduction recommendations. Clean Architecture, Azure AI Search semantic factor lookup, 88 automated tests. Built for EU CSRD Scope 3 compliance." }, "skills": { "label": "04 — SKILLS", diff --git a/src/messages/th.json b/src/messages/th.json index 316bcaa..2dcf47f 100644 --- a/src/messages/th.json +++ b/src/messages/th.json @@ -14,7 +14,7 @@ "resume": "เรซูเม่" }, "hero": { - "subtitle": "FULL-STACK AI ENGINEER · STATION F · PARIS", + "subtitle": "ผู้ก่อตั้ง · วิศวกร FULL-STACK & AI · ปารีส", "specialties": "AI Engineering · Full-Stack Systems · Backend & Cloud Data", "openTo": "OPEN TO AI / FULL-STACK / BACKEND ROLES · FR / DE / UK", "viewWork": "ดูผลงาน", @@ -26,7 +26,7 @@ "heading": "AI Engineer · Full-Stack ·", "headingEm": "Backend Systems", "quote": "AI Engineer · Full-Stack · Backend Systems — building production-grade software at the intersection of telecom, healthcare, and finance, across Asia and Europe.", - "p1": "Currently a Full-Stack AI Engineer at Siloett.AI (Station F, Paris), where I architect end-to-end Generative AI systems on Azure with FastAPI, Azure Functions, and React/TypeScript.", + "p1": "ปัจจุบันเป็นผู้ก่อตั้ง Ekkhara สตูดิโอซอฟต์แวร์และ AI ที่ลงทุนด้วยตนเอง สร้าง EdTech เพื่อเมียนมา — ล่าสุดคือ SpeakProof บอทฝึก TOEFL ที่ทำงานบน Telegram โดยตรงและใช้งานได้โดยไม่ต้องมี VPN ก่อนหน้านี้เป็นวิศวกร Full-Stack AI ที่ Siloett.AI (Station F, ปารีส) ออกแบบระบบ Generative AI แบบครบวงจรบน Azure ด้วย FastAPI และ React/TypeScript", "p2": "Beyond AI, my engineering portfolio spans backend systems — Java 21, Spring Boot 3.5, Kafka, microservices — and cloud data engineering on AWS, Snowflake, Databricks, dbt, and Airflow. Telecom domain depth includes CDR pipelines, SMPP gateways, and Diameter Credit-Control.", "p3": "Dual Master's degrees from Telecom SudParis (Paris) and AIT (Bangkok), plus 5+ years shipping production software across healthcare, RegTech, telecom, and smart-city domains.", "p4": "Currently exploring AI Engineer, Full-Stack, and Backend Engineer roles across France, Germany, and the UK. If you're hiring or know of a fit — let's talk.", @@ -40,37 +40,43 @@ "label": "02 — EXPERIENCE", "heading": "ที่ที่ผมได้", "headingEm": "สร้างและเรียนรู้", - "0_job": "วิศวกร AI Full-Stack", - "0_badge": "AI Safety & Compliance · Station F · ปารีส", - "0_date": "Jun 2025 — May 2026", - "0_pt0": "ออกแบบสถาปัตยกรรมและสร้างแพลตฟอร์ม Generative AI ตั้งแต่เริ่มต้น — LLM orchestration, RAG pipelines และ frontend ระดับ production ด้วย React/TypeScript พร้อม backend แบบ serverless ด้วย Python (FastAPI) และ Azure Functions", - "0_pt1": "ออกแบบและพัฒนาชั้นการตรวจสอบ Responsible AI รวมถึงฟิลเตอร์ความปลอดภัยของเนื้อหา การตรวจจับอคติ และ guardrails ด้านการปฏิบัติตามกฎระเบียบ เพื่อให้แน่ใจว่าผลลัพธ์ที่สร้างโดย AI ทั้งหมดเป็นไปตามมาตรฐานกฎระเบียบและจริยธรรม", - "0_pt2": "สร้างระบบ AI safety และการปฏิบัติตามทรัพย์สินทางปัญญา รวมถึง audit logging, provenance tracking และ output attribution pipelines — เพื่อให้มั่นใจว่าวงจรชีวิตของผลลัพธ์ AI สามารถตรวจสอบย้อนกลับได้และมีความรับผิดชอบ", - "0_pt3": "พัฒนา framework สำหรับ prompt engineering และการประเมิน LLM โดยใช้ Azure OpenAI GPT-4o และ LangChain พร้อมการ fine-tuning อย่างเป็นระบบเพื่อเพิ่มประสิทธิภาพความถูกต้องเฉพาะทางใน use case ด้าน compliance", - "1_job": "วิทยาการข้อมูล / วิศวกรข้อมูลคลาวด์", - "1_badge": "Station F · ปารีส", - "1_date": "Jul 2024 — Dec 2025", - "1_pt0": "ออกแบบ pipeline การประมวลผลข้อมูลแบบ batch บนคลาวด์โดยใช้ Microsoft Azure Batch และ Docker สำหรับการวิเคราะห์การเดินทางในเมือง", - "1_pt1": "ทำให้ workflow ของ Computer Vision และเซ็นเซอร์ Bluetooth เป็นอัตโนมัติ เพื่อให้ได้ข้อมูลเชิงลึกด้าน smart city แบบ real-time ที่ปรับขนาดได้", - "1_pt2": "ส่งมอบแดชบอร์ดวิเคราะห์ระดับ production ที่ถูกนำไปใช้โดยรัฐบาลเมืองและผู้มีส่วนได้ส่วนเสียด้านการขนส่ง", - "2_job": "วิศวกรวิจัยและ Back-End", - "2_badge": "Computer Vision · Backend AI", - "2_date": "Aug 2023 — Jul 2024", - "2_pt0": "พัฒนา back-end services และ data pipelines ให้กับห้องปฏิบัติการวิจัยที่ส่งมอบความสามารถ AI ประยุกต์ให้แก่องค์กรพันธมิตร — นำงานวิจัย computer vision และ NLP ขึ้น production ผ่าน Python API", - "2_pt1": "สร้างระบบแปลภาษาอังกฤษ–พม่าแบบครบวงจรบน corpus WikiHow ระดับ gold จำนวน 10K ที่คัดสรรด้วยมือ — ดูแลตั้งแต่การสร้างชุดข้อมูล การฝึกโมเดล การประเมิน จนถึงการ deploy หลัง public API", - "2_pt2": "พัฒนา research prototype ใหม่ๆ ด้าน computer vision และ NLP หลายภาษา พร้อม back-end infrastructure สำหรับให้บริการ — เปลี่ยนงานวิจัยของห้องแล็บให้เป็นเครื่องมือที่ทำซ้ำและ deploy ได้", + "0_job": "ผู้ก่อตั้ง & วิศวกร Full-Stack / AI", + "0_badge": "ผู้ก่อตั้ง · EdTech เพื่อเมียนมา", + "0_date": "May 2026 — Present", + "0_pt0": "ก่อตั้ง Ekkhara สตูดิโอซอฟต์แวร์และ AI ที่ลงทุนด้วยตนเอง สร้างผลิตภัณฑ์ EdTech เพื่อเมียนมา — นำแต่ละผลิตภัณฑ์จากไอเดียสู่การใช้งานจริง พร้อมดูแลสถาปัตยกรรม แบ็กเอนด์ AI และฟรอนต์เอนด์แบบครบวงจร", + "0_pt1": "สร้าง SpeakProof บอทฝึกพูด TOEFL และฝึกภาษาอังกฤษที่ทำงานภายใน Telegram ทั้งหมด — ให้ผู้เรียนชาวเมียนมาเตรียมสอบ TOEFL (แบบคอมพิวเตอร์) จากแอปที่ใช้อยู่ทุกวัน โดยไม่ต้องใช้ VPN แม้ประเทศจะจำกัดการเข้าถึงอินเทอร์เน็ต", + "0_pt2": "พัฒนาฟูลสแตกเบื้องหลังทุกผลิตภัณฑ์ — เซอร์วิส Python / FastAPI, ฟีดแบ็กและการให้คะแนนด้วย LLM และ UX แบบสนทนา — ส่งมอบเครื่องมือ AI ที่เข้าถึงผู้ใช้ในที่ที่การเข้าถึงและโครงสร้างพื้นฐานจำกัด", + "1_job": "วิศวกร AI Full-Stack", + "1_badge": "AI Safety & Compliance · Station F · ปารีส", + "1_date": "Jun 2025 — May 2026", + "1_pt0": "ออกแบบสถาปัตยกรรมและสร้างแพลตฟอร์ม Generative AI ตั้งแต่เริ่มต้น — LLM orchestration, RAG pipelines และ frontend ระดับ production ด้วย React/TypeScript พร้อม backend แบบ serverless ด้วย Python (FastAPI) และ Azure Functions", + "1_pt1": "ออกแบบและพัฒนาชั้นการตรวจสอบ Responsible AI รวมถึงฟิลเตอร์ความปลอดภัยของเนื้อหา การตรวจจับอคติ และ guardrails ด้านการปฏิบัติตามกฎระเบียบ เพื่อให้แน่ใจว่าผลลัพธ์ที่สร้างโดย AI ทั้งหมดเป็นไปตามมาตรฐานกฎระเบียบและจริยธรรม", + "1_pt2": "สร้างระบบ AI safety และการปฏิบัติตามทรัพย์สินทางปัญญา รวมถึง audit logging, provenance tracking และ output attribution pipelines — เพื่อให้มั่นใจว่าวงจรชีวิตของผลลัพธ์ AI สามารถตรวจสอบย้อนกลับได้และมีความรับผิดชอบ", + "1_pt3": "พัฒนา framework สำหรับ prompt engineering และการประเมิน LLM โดยใช้ Azure OpenAI GPT-4o และ LangChain พร้อมการ fine-tuning อย่างเป็นระบบเพื่อเพิ่มประสิทธิภาพความถูกต้องเฉพาะทางใน use case ด้าน compliance", + "2_job": "วิทยาการข้อมูล / วิศวกรข้อมูลคลาวด์", + "2_badge": "Station F · ปารีส", + "2_date": "Jul 2024 — Dec 2025", + "2_pt0": "ออกแบบ pipeline การประมวลผลข้อมูลแบบ batch บนคลาวด์โดยใช้ Microsoft Azure Batch และ Docker สำหรับการวิเคราะห์การเดินทางในเมือง", + "2_pt1": "ทำให้ workflow ของ Computer Vision และเซ็นเซอร์ Bluetooth เป็นอัตโนมัติ เพื่อให้ได้ข้อมูลเชิงลึกด้าน smart city แบบ real-time ที่ปรับขนาดได้", + "2_pt2": "ส่งมอบแดชบอร์ดวิเคราะห์ระดับ production ที่ถูกนำไปใช้โดยรัฐบาลเมืองและผู้มีส่วนได้ส่วนเสียด้านการขนส่ง", "3_job": "วิศวกรวิจัยและ Back-End", - "3_badge": "ห้องแล็บ AI ประยุกต์ · Backend", - "3_date": "Jan 2023 — Aug 2023", - "3_pt0": "สร้างเครื่องมือ NLP paraphrasing แบบครบวงจรในห้องปฏิบัติการวิจัยที่ให้บริการ AI ประยุกต์แก่บริษัทต่างๆ — ตั้งแต่การพัฒนาโมเดลจนถึง back-end API", - "3_pt1": "ออกแบบชั้นข้อมูล — ทำความสะอาดและจัดโครงสร้างชุดข้อมูลฝึก — และปรับปรุง workflow การฝึก เพิ่มความแม่นยำของโมเดลขึ้น 15%", - "3_pt2": "ดูแล back-end operations ของเครื่องมือ AI ในห้องแล็บ เสริมสร้างการจัดการข้อมูลและการปฏิบัติด้านวิศวกรรม R&D", - "4_job": "วิศวกรซอฟต์แวร์ (Web)", - "4_badge": "Full-Stack Web · หน่วยงาน UN", - "4_date": "Jan 2021 — Dec 2022", - "4_pt0": "พัฒนาเว็บแอปพลิเคชันแบบ full-stack ให้กับหน่วยงานของ UN (FAO) — แดชบอร์ดข้อมูลภายในและพอร์ทัลสาธารณะที่ส่งมอบข้อมูลโครงการด้านเกษตรและความมั่นคงทางอาหารให้กับเจ้าหน้าที่และทีมภาคสนาม", - "4_pt1": "ออกแบบเครื่องมือเก็บข้อมูลภาคสนามและ back-end APIs ที่อยู่เบื้องหลัง ทำให้เจ้าหน้าที่ภาคสนามสามารถบันทึก ตรวจสอบ และซิงค์ข้อมูลโครงการเข้าสู่ระบบรายงานส่วนกลางได้", - "4_pt2": "ดูแลฟีเจอร์แบบ end-to-end ตลอดทั้ง stack — front-ends ด้วย React/Next.js + TypeScript และ back-ends ด้วย Python และ PHP/CMS — ตั้งแต่ data model และ REST API จนถึง UI ที่ deploy แล้ว" + "3_badge": "Computer Vision · Backend AI", + "3_date": "Aug 2023 — Jul 2024", + "3_pt0": "พัฒนา back-end services และ data pipelines ให้กับห้องปฏิบัติการวิจัยที่ส่งมอบความสามารถ AI ประยุกต์ให้แก่องค์กรพันธมิตร — นำงานวิจัย computer vision และ NLP ขึ้น production ผ่าน Python API", + "3_pt1": "สร้างระบบแปลภาษาอังกฤษ–พม่าแบบครบวงจรบน corpus WikiHow ระดับ gold จำนวน 10K ที่คัดสรรด้วยมือ — ดูแลตั้งแต่การสร้างชุดข้อมูล การฝึกโมเดล การประเมิน จนถึงการ deploy หลัง public API", + "3_pt2": "พัฒนา research prototype ใหม่ๆ ด้าน computer vision และ NLP หลายภาษา พร้อม back-end infrastructure สำหรับให้บริการ — เปลี่ยนงานวิจัยของห้องแล็บให้เป็นเครื่องมือที่ทำซ้ำและ deploy ได้", + "4_job": "วิศวกรวิจัยและ Back-End", + "4_badge": "ห้องแล็บ AI ประยุกต์ · Backend", + "4_date": "Jan 2023 — Aug 2023", + "4_pt0": "สร้างเครื่องมือ NLP paraphrasing แบบครบวงจรในห้องปฏิบัติการวิจัยที่ให้บริการ AI ประยุกต์แก่บริษัทต่างๆ — ตั้งแต่การพัฒนาโมเดลจนถึง back-end API", + "4_pt1": "ออกแบบชั้นข้อมูล — ทำความสะอาดและจัดโครงสร้างชุดข้อมูลฝึก — และปรับปรุง workflow การฝึก เพิ่มความแม่นยำของโมเดลขึ้น 15%", + "4_pt2": "ดูแล back-end operations ของเครื่องมือ AI ในห้องแล็บ เสริมสร้างการจัดการข้อมูลและการปฏิบัติด้านวิศวกรรม R&D", + "5_job": "วิศวกรซอฟต์แวร์ (Web)", + "5_badge": "Full-Stack Web · หน่วยงาน UN", + "5_date": "Jan 2021 — Dec 2022", + "5_pt0": "พัฒนาเว็บแอปพลิเคชันแบบ full-stack ให้กับหน่วยงานของ UN (FAO) — แดชบอร์ดข้อมูลภายในและพอร์ทัลสาธารณะที่ส่งมอบข้อมูลโครงการด้านเกษตรและความมั่นคงทางอาหารให้กับเจ้าหน้าที่และทีมภาคสนาม", + "5_pt1": "ออกแบบเครื่องมือเก็บข้อมูลภาคสนามและ back-end APIs ที่อยู่เบื้องหลัง ทำให้เจ้าหน้าที่ภาคสนามสามารถบันทึก ตรวจสอบ และซิงค์ข้อมูลโครงการเข้าสู่ระบบรายงานส่วนกลางได้", + "5_pt2": "ดูแลฟีเจอร์แบบ end-to-end ตลอดทั้ง stack — front-ends ด้วย React/Next.js + TypeScript และ back-ends ด้วย Python และ PHP/CMS — ตั้งแต่ data model และ REST API จนถึง UI ที่ deploy แล้ว" }, "projects": { "label": "03 — PROJECTS", @@ -83,19 +89,21 @@ "demo": "เดโม", "gh": "GH", "liveAtVercel": "LIVE ON VERCEL", + "liveAtTelegram": "LIVE ON TELEGRAM", "openSourceOnGithub": "OPEN-SOURCE ON GITHUB", - "0_desc": "Real-time European grid lakehouse on AWS — probabilistic load forecasting (DeepAR / quantile loss) and stochastic optimisation for battery flexibility decisions. Medallion architecture on S3 + Iceberg, MSK Kafka streaming, dbt models, Airflow orchestration, MLflow tracking. Cloud Data Engineering portfolio piece.", - "1_desc": "Event-driven Call Detail Record ingestion, rating, and reconciliation pipeline simulating an MVNO billing back-end. Idempotent Kafka consumers, Spring Boot 3.5 microservices, MySQL for rated CDRs, MongoDB for raw events, Docker Compose for local infra. Built around real telecom domain models (3GPP TS 32.298).", - "2_desc": "End-to-end CSRD/ESRS sustainability data pipeline — Claude/Mistral GenAI extraction from sustainability reports with page-level audit lineage, Snowflake warehouse (validated) + DuckDB local dev, dbt transformations, Airflow orchestration. Built for EU corporate sustainability reporting compliance.", - "3_desc": "AI-powered blood test interpretation for personalised supplement guidance — competing at Haleon VivaTech 2026. OCR ingestion of French lab reports, validated biomarker classification, longitudinal tracking, and supplement recommendations grounded in clinical evidence. Real-data moat through partner lab integrations.", - "4_desc": "From-scratch ReAct Agent Observatory — observe, debug, and benchmark LLM agents with a built-in 8-type failure taxonomy (hallucinated tools, malformed actions, context overflow, goal drift, …) and multi-provider eval harness (Groq, OpenAI, Anthropic, Google, Ollama). Composite scoring (answer + tools + efficiency + reliability), Clean Architecture FastAPI + PostgreSQL backend, Next.js 16 frontend with real-time SSE streaming. 50+ benchmark cases, 81 tests.", - "5_desc": "Real-World Evidence platform for vaccine research — full-stack application for ingesting, analyzing, and visualizing vaccine safety and efficacy data from real-world sources at scale. Built at Siloett.AI for healthcare and life-sciences buyers.", - "6_desc": "Diameter Credit-Control Server (Gy / RFC 4006 / App-Id 4) for real-time prepaid mobile billing. Idempotent partial debits, jdiameter 1.7.x stack, designed against TRANSATEL/MVNO production patterns.", - "7_desc": "Java SMPP v3.4 gateway bridging inbound SMS (submit_sm) to RabbitMQ for downstream processing. Spring Boot 3.5 + jsmpp 3.0, dockerised, designed for MVNO and telecom messaging platforms.", - "8_desc": "Real-time urban mobility analytics on TimescaleDB + PostGIS + Uber H3. Spring Boot ingestion, Kafka stream processing, Server-Sent Events for live dashboards. Smart-city back-end blueprint.", - "9_desc": "Reference implementation of the BCBS 239 risk-data-aggregation lakehouse pattern on Databricks + Delta Lake + Unity Catalog + dbt-databricks. MIT-licensed, synthetic data only — banking risk-data engineering portfolio piece.", - "10_desc": "Serverless middleware enforcing responsible-AI compliance on LLM applications — PII detection, bias screening, hate-speech filtering, and RAG-powered policy enforcement on top of Azure OpenAI.", - "11_desc": "Cloud Carbon Intelligence platform estimating CO2e emissions from Azure infrastructure with AI-powered reduction recommendations. Clean Architecture, Azure AI Search semantic factor lookup, 88 automated tests. Built for EU CSRD Scope 3 compliance." + "0_desc": "Telegram-native TOEFL speaking & English-practice bot for Myanmar learners — drill toward the TOEFL computer-based test inside an app people already use daily, with zero VPN needed despite nationwide internet restrictions. LLM-powered speaking feedback and scoring on a Python / FastAPI backend. An Ekkhara EdTech product.", + "1_desc": "Real-time European grid lakehouse on AWS — probabilistic load forecasting (DeepAR / quantile loss) and stochastic optimisation for battery flexibility decisions. Medallion architecture on S3 + Iceberg, MSK Kafka streaming, dbt models, Airflow orchestration, MLflow tracking. Cloud Data Engineering portfolio piece.", + "2_desc": "Event-driven Call Detail Record ingestion, rating, and reconciliation pipeline simulating an MVNO billing back-end. Idempotent Kafka consumers, Spring Boot 3.5 microservices, MySQL for rated CDRs, MongoDB for raw events, Docker Compose for local infra. Built around real telecom domain models (3GPP TS 32.298).", + "3_desc": "End-to-end CSRD/ESRS sustainability data pipeline — Claude/Mistral GenAI extraction from sustainability reports with page-level audit lineage, Snowflake warehouse (validated) + DuckDB local dev, dbt transformations, Airflow orchestration. Built for EU corporate sustainability reporting compliance.", + "4_desc": "AI-powered blood test interpretation for personalised supplement guidance — competing at Haleon VivaTech 2026. OCR ingestion of French lab reports, validated biomarker classification, longitudinal tracking, and supplement recommendations grounded in clinical evidence. Real-data moat through partner lab integrations.", + "5_desc": "From-scratch ReAct Agent Observatory — observe, debug, and benchmark LLM agents with a built-in 8-type failure taxonomy (hallucinated tools, malformed actions, context overflow, goal drift, …) and multi-provider eval harness (Groq, OpenAI, Anthropic, Google, Ollama). Composite scoring (answer + tools + efficiency + reliability), Clean Architecture FastAPI + PostgreSQL backend, Next.js 16 frontend with real-time SSE streaming. 50+ benchmark cases, 81 tests.", + "6_desc": "Real-World Evidence platform for vaccine research — full-stack application for ingesting, analyzing, and visualizing vaccine safety and efficacy data from real-world sources at scale. Built at Siloett.AI for healthcare and life-sciences buyers.", + "7_desc": "Diameter Credit-Control Server (Gy / RFC 4006 / App-Id 4) for real-time prepaid mobile billing. Idempotent partial debits, jdiameter 1.7.x stack, designed against TRANSATEL/MVNO production patterns.", + "8_desc": "Java SMPP v3.4 gateway bridging inbound SMS (submit_sm) to RabbitMQ for downstream processing. Spring Boot 3.5 + jsmpp 3.0, dockerised, designed for MVNO and telecom messaging platforms.", + "9_desc": "Real-time urban mobility analytics on TimescaleDB + PostGIS + Uber H3. Spring Boot ingestion, Kafka stream processing, Server-Sent Events for live dashboards. Smart-city back-end blueprint.", + "10_desc": "Reference implementation of the BCBS 239 risk-data-aggregation lakehouse pattern on Databricks + Delta Lake + Unity Catalog + dbt-databricks. MIT-licensed, synthetic data only — banking risk-data engineering portfolio piece.", + "11_desc": "Serverless middleware enforcing responsible-AI compliance on LLM applications — PII detection, bias screening, hate-speech filtering, and RAG-powered policy enforcement on top of Azure OpenAI.", + "12_desc": "Cloud Carbon Intelligence platform estimating CO2e emissions from Azure infrastructure with AI-powered reduction recommendations. Clean Architecture, Azure AI Search semantic factor lookup, 88 automated tests. Built for EU CSRD Scope 3 compliance." }, "skills": { "label": "04 — SKILLS", diff --git a/src/messages/zh.json b/src/messages/zh.json index 49ed8eb..0017e85 100644 --- a/src/messages/zh.json +++ b/src/messages/zh.json @@ -14,7 +14,7 @@ "resume": "简历" }, "hero": { - "subtitle": "FULL-STACK AI ENGINEER · STATION F · PARIS", + "subtitle": "创始人 · 全栈 & AI 工程师 · 巴黎", "specialties": "AI Engineering · Full-Stack Systems · Backend & Cloud Data", "openTo": "OPEN TO AI / FULL-STACK / BACKEND ROLES · FR / DE / UK", "viewWork": "查看作品", @@ -26,7 +26,7 @@ "heading": "AI Engineer · Full-Stack ·", "headingEm": "Backend Systems", "quote": "AI Engineer · Full-Stack · Backend Systems — building production-grade software at the intersection of telecom, healthcare, and finance, across Asia and Europe.", - "p1": "Currently a Full-Stack AI Engineer at Siloett.AI (Station F, Paris), where I architect end-to-end Generative AI systems on Azure with FastAPI, Azure Functions, and React/TypeScript.", + "p1": "目前是 Ekkhara 的创始人——一家自筹资金的软件与 AI 工作室，为缅甸打造 EdTech 产品，最新作品是 SpeakProof：一个原生于 Telegram、无需 VPN 即可使用的 TOEFL 练习机器人。此前，我在 Siloett.AI（巴黎 Station F）担任全栈 AI 工程师，使用 FastAPI 与 React/TypeScript 在 Azure 上构建端到端生成式 AI 系统。", "p2": "Beyond AI, my engineering portfolio spans backend systems — Java 21, Spring Boot 3.5, Kafka, microservices — and cloud data engineering on AWS, Snowflake, Databricks, dbt, and Airflow. Telecom domain depth includes CDR pipelines, SMPP gateways, and Diameter Credit-Control.", "p3": "Dual Master's degrees from Telecom SudParis (Paris) and AIT (Bangkok), plus 5+ years shipping production software across healthcare, RegTech, telecom, and smart-city domains.", "p4": "Currently exploring AI Engineer, Full-Stack, and Backend Engineer roles across France, Germany, and the UK. If you're hiring or know of a fit — let's talk.", @@ -40,37 +40,43 @@ "label": "02 — EXPERIENCE", "heading": "我在哪里", "headingEm": "构建与学习", - "0_job": "全栈AI工程师", - "0_badge": "AI安全与合规 · Station F · 巴黎", - "0_date": "Jun 2025 — May 2026", - "0_pt0": "从零开始架构并构建了端到端生成式AI平台 — LLM编排、RAG管道，以及使用 Python（FastAPI）和 Azure Functions 无服务器后端的生产级 React/TypeScript 前端", - "0_pt1": "设计并实施了负责任AI验证层，包括内容安全过滤器、偏见检测检查和合规护栏，确保所有AI生成的输出符合监管和伦理标准", - "0_pt2": "构建了AI安全和知识产权合规系统，包括审计日志、来源追踪和输出归因管道 — 确保可追溯和可问责的AI输出生命周期", - "0_pt3": "使用 Azure OpenAI GPT-4o 和 LangChain 开发了提示工程和 LLM 评估框架，通过系统微调优化合规用例的领域准确性", - "1_job": "数据科学 / 云数据工程师", - "1_badge": "Station F · 巴黎", - "1_date": "Jul 2024 — Dec 2025", - "1_pt0": "使用 Microsoft Azure Batch 和 Docker 设计了基于云的批量数据处理管道，用于城市交通分析", - "1_pt1": "自动化了计算机视觉和蓝牙传感器工作流，实现可扩展的实时智慧城市洞察", - "1_pt2": "交付了被市政府和交通利益相关方采用的生产级分析仪表板", - "2_job": "研究与后端工程师", - "2_badge": "计算机视觉 · 后端AI", - "2_date": "Aug 2023 — Jul 2024", - "2_pt0": "为一家向合作机构提供应用型AI能力的研究实验室构建后端服务与数据管道 — 将计算机视觉与NLP研究通过Python API投入生产", - "2_pt1": "在手动构建并整理的 10K 黄金标注 WikiHow 平行语料库上构建了完整的英缅机器翻译系统 — 负责数据集构建、模型训练、评估到公共API部署", - "2_pt2": "在计算机视觉和多语言NLP领域开发新颖的研究原型，并搭建为其提供服务的后端基础设施 — 将实验室研究转化为可复现、可部署的工具", + "0_job": "创始人 & 全栈 / AI 工程师", + "0_badge": "创始人 · 面向缅甸的教育科技", + "0_date": "May 2026 — Present", + "0_pt0": "创立 Ekkhara，一家自筹资金的软件与 AI 工作室，为缅甸打造 EdTech 产品——每款产品从构想到上线，全程负责架构、后端、AI 与前端。", + "0_pt1": "构建 SpeakProof——一个完全运行在 Telegram 内的 TOEFL 口语与英语练习机器人，让缅甸学习者无需 VPN，即可在每天都在用的应用中备战 TOEFL 机考，绕开该国的网络限制。", + "0_pt2": "负责每款产品背后的完整技术栈——Python / FastAPI 服务、由 LLM 驱动的反馈与评分，以及对话式 UX——交付能够触达受限网络与基础设施环境用户的 AI 工具。", + "1_job": "全栈AI工程师", + "1_badge": "AI安全与合规 · Station F · 巴黎", + "1_date": "Jun 2025 — May 2026", + "1_pt0": "从零开始架构并构建了端到端生成式AI平台 — LLM编排、RAG管道，以及使用 Python（FastAPI）和 Azure Functions 无服务器后端的生产级 React/TypeScript 前端", + "1_pt1": "设计并实施了负责任AI验证层，包括内容安全过滤器、偏见检测检查和合规护栏，确保所有AI生成的输出符合监管和伦理标准", + "1_pt2": "构建了AI安全和知识产权合规系统，包括审计日志、来源追踪和输出归因管道 — 确保可追溯和可问责的AI输出生命周期", + "1_pt3": "使用 Azure OpenAI GPT-4o 和 LangChain 开发了提示工程和 LLM 评估框架，通过系统微调优化合规用例的领域准确性", + "2_job": "数据科学 / 云数据工程师", + "2_badge": "Station F · 巴黎", + "2_date": "Jul 2024 — Dec 2025", + "2_pt0": "使用 Microsoft Azure Batch 和 Docker 设计了基于云的批量数据处理管道，用于城市交通分析", + "2_pt1": "自动化了计算机视觉和蓝牙传感器工作流，实现可扩展的实时智慧城市洞察", + "2_pt2": "交付了被市政府和交通利益相关方采用的生产级分析仪表板", "3_job": "研究与后端工程师", - "3_badge": "应用AI实验室 · 后端", - "3_date": "Jan 2023 — Aug 2023", - "3_pt0": "在一家向企业提供应用型AI服务的研究实验室，端到端构建了一款 NLP 释义工具 — 从模型到后端API", - "3_pt1": "搭建数据层 — 清洗并结构化训练数据集 — 并优化训练流程，将模型准确率提高了15%", - "3_pt2": "负责实验室AI工具的后端运维，强化数据管理与研发工程实践", - "4_job": "软件工程师（Web）", - "4_badge": "全栈 Web · 联合国机构", - "4_date": "Jan 2021 — Dec 2022", - "4_pt0": "为联合国机构（FAO）构建全栈 Web 应用 — 开发面向员工与现场团队、交付农业与粮食安全项目数据的内部数据看板与公开门户", - "4_pt1": "设计现场数据采集工具及其背后的后端 API，使现场人员能够采集、校验并将项目数据同步至中央报表系统", - "4_pt2": "在整个技术栈中端到端负责功能 — React/Next.js + TypeScript 前端与 Python、PHP/CMS 后端 — 从数据模型、REST API 到部署上线的 UI" + "3_badge": "计算机视觉 · 后端AI", + "3_date": "Aug 2023 — Jul 2024", + "3_pt0": "为一家向合作机构提供应用型AI能力的研究实验室构建后端服务与数据管道 — 将计算机视觉与NLP研究通过Python API投入生产", + "3_pt1": "在手动构建并整理的 10K 黄金标注 WikiHow 平行语料库上构建了完整的英缅机器翻译系统 — 负责数据集构建、模型训练、评估到公共API部署", + "3_pt2": "在计算机视觉和多语言NLP领域开发新颖的研究原型，并搭建为其提供服务的后端基础设施 — 将实验室研究转化为可复现、可部署的工具", + "4_job": "研究与后端工程师", + "4_badge": "应用AI实验室 · 后端", + "4_date": "Jan 2023 — Aug 2023", + "4_pt0": "在一家向企业提供应用型AI服务的研究实验室，端到端构建了一款 NLP 释义工具 — 从模型到后端API", + "4_pt1": "搭建数据层 — 清洗并结构化训练数据集 — 并优化训练流程，将模型准确率提高了15%", + "4_pt2": "负责实验室AI工具的后端运维，强化数据管理与研发工程实践", + "5_job": "软件工程师（Web）", + "5_badge": "全栈 Web · 联合国机构", + "5_date": "Jan 2021 — Dec 2022", + "5_pt0": "为联合国机构（FAO）构建全栈 Web 应用 — 开发面向员工与现场团队、交付农业与粮食安全项目数据的内部数据看板与公开门户", + "5_pt1": "设计现场数据采集工具及其背后的后端 API，使现场人员能够采集、校验并将项目数据同步至中央报表系统", + "5_pt2": "在整个技术栈中端到端负责功能 — React/Next.js + TypeScript 前端与 Python、PHP/CMS 后端 — 从数据模型、REST API 到部署上线的 UI" }, "projects": { "label": "03 — PROJECTS", @@ -83,19 +89,21 @@ "demo": "演示", "gh": "GH", "liveAtVercel": "LIVE ON VERCEL", + "liveAtTelegram": "LIVE ON TELEGRAM", "openSourceOnGithub": "OPEN-SOURCE ON GITHUB", - "0_desc": "Real-time European grid lakehouse on AWS — probabilistic load forecasting (DeepAR / quantile loss) and stochastic optimisation for battery flexibility decisions. Medallion architecture on S3 + Iceberg, MSK Kafka streaming, dbt models, Airflow orchestration, MLflow tracking. Cloud Data Engineering portfolio piece.", - "1_desc": "Event-driven Call Detail Record ingestion, rating, and reconciliation pipeline simulating an MVNO billing back-end. Idempotent Kafka consumers, Spring Boot 3.5 microservices, MySQL for rated CDRs, MongoDB for raw events, Docker Compose for local infra. Built around real telecom domain models (3GPP TS 32.298).", - "2_desc": "End-to-end CSRD/ESRS sustainability data pipeline — Claude/Mistral GenAI extraction from sustainability reports with page-level audit lineage, Snowflake warehouse (validated) + DuckDB local dev, dbt transformations, Airflow orchestration. Built for EU corporate sustainability reporting compliance.", - "3_desc": "AI-powered blood test interpretation for personalised supplement guidance — competing at Haleon VivaTech 2026. OCR ingestion of French lab reports, validated biomarker classification, longitudinal tracking, and supplement recommendations grounded in clinical evidence. Real-data moat through partner lab integrations.", - "4_desc": "From-scratch ReAct Agent Observatory — observe, debug, and benchmark LLM agents with a built-in 8-type failure taxonomy (hallucinated tools, malformed actions, context overflow, goal drift, …) and multi-provider eval harness (Groq, OpenAI, Anthropic, Google, Ollama). Composite scoring (answer + tools + efficiency + reliability), Clean Architecture FastAPI + PostgreSQL backend, Next.js 16 frontend with real-time SSE streaming. 50+ benchmark cases, 81 tests.", - "5_desc": "Real-World Evidence platform for vaccine research — full-stack application for ingesting, analyzing, and visualizing vaccine safety and efficacy data from real-world sources at scale. Built at Siloett.AI for healthcare and life-sciences buyers.", - "6_desc": "Diameter Credit-Control Server (Gy / RFC 4006 / App-Id 4) for real-time prepaid mobile billing. Idempotent partial debits, jdiameter 1.7.x stack, designed against TRANSATEL/MVNO production patterns.", - "7_desc": "Java SMPP v3.4 gateway bridging inbound SMS (submit_sm) to RabbitMQ for downstream processing. Spring Boot 3.5 + jsmpp 3.0, dockerised, designed for MVNO and telecom messaging platforms.", - "8_desc": "Real-time urban mobility analytics on TimescaleDB + PostGIS + Uber H3. Spring Boot ingestion, Kafka stream processing, Server-Sent Events for live dashboards. Smart-city back-end blueprint.", - "9_desc": "Reference implementation of the BCBS 239 risk-data-aggregation lakehouse pattern on Databricks + Delta Lake + Unity Catalog + dbt-databricks. MIT-licensed, synthetic data only — banking risk-data engineering portfolio piece.", - "10_desc": "Serverless middleware enforcing responsible-AI compliance on LLM applications — PII detection, bias screening, hate-speech filtering, and RAG-powered policy enforcement on top of Azure OpenAI.", - "11_desc": "Cloud Carbon Intelligence platform estimating CO2e emissions from Azure infrastructure with AI-powered reduction recommendations. Clean Architecture, Azure AI Search semantic factor lookup, 88 automated tests. Built for EU CSRD Scope 3 compliance." + "0_desc": "Telegram-native TOEFL speaking & English-practice bot for Myanmar learners — drill toward the TOEFL computer-based test inside an app people already use daily, with zero VPN needed despite nationwide internet restrictions. LLM-powered speaking feedback and scoring on a Python / FastAPI backend. An Ekkhara EdTech product.", + "1_desc": "Real-time European grid lakehouse on AWS — probabilistic load forecasting (DeepAR / quantile loss) and stochastic optimisation for battery flexibility decisions. Medallion architecture on S3 + Iceberg, MSK Kafka streaming, dbt models, Airflow orchestration, MLflow tracking. Cloud Data Engineering portfolio piece.", + "2_desc": "Event-driven Call Detail Record ingestion, rating, and reconciliation pipeline simulating an MVNO billing back-end. Idempotent Kafka consumers, Spring Boot 3.5 microservices, MySQL for rated CDRs, MongoDB for raw events, Docker Compose for local infra. Built around real telecom domain models (3GPP TS 32.298).", + "3_desc": "End-to-end CSRD/ESRS sustainability data pipeline — Claude/Mistral GenAI extraction from sustainability reports with page-level audit lineage, Snowflake warehouse (validated) + DuckDB local dev, dbt transformations, Airflow orchestration. Built for EU corporate sustainability reporting compliance.", + "4_desc": "AI-powered blood test interpretation for personalised supplement guidance — competing at Haleon VivaTech 2026. OCR ingestion of French lab reports, validated biomarker classification, longitudinal tracking, and supplement recommendations grounded in clinical evidence. Real-data moat through partner lab integrations.", + "5_desc": "From-scratch ReAct Agent Observatory — observe, debug, and benchmark LLM agents with a built-in 8-type failure taxonomy (hallucinated tools, malformed actions, context overflow, goal drift, …) and multi-provider eval harness (Groq, OpenAI, Anthropic, Google, Ollama). Composite scoring (answer + tools + efficiency + reliability), Clean Architecture FastAPI + PostgreSQL backend, Next.js 16 frontend with real-time SSE streaming. 50+ benchmark cases, 81 tests.", + "6_desc": "Real-World Evidence platform for vaccine research — full-stack application for ingesting, analyzing, and visualizing vaccine safety and efficacy data from real-world sources at scale. Built at Siloett.AI for healthcare and life-sciences buyers.", + "7_desc": "Diameter Credit-Control Server (Gy / RFC 4006 / App-Id 4) for real-time prepaid mobile billing. Idempotent partial debits, jdiameter 1.7.x stack, designed against TRANSATEL/MVNO production patterns.", + "8_desc": "Java SMPP v3.4 gateway bridging inbound SMS (submit_sm) to RabbitMQ for downstream processing. Spring Boot 3.5 + jsmpp 3.0, dockerised, designed for MVNO and telecom messaging platforms.", + "9_desc": "Real-time urban mobility analytics on TimescaleDB + PostGIS + Uber H3. Spring Boot ingestion, Kafka stream processing, Server-Sent Events for live dashboards. Smart-city back-end blueprint.", + "10_desc": "Reference implementation of the BCBS 239 risk-data-aggregation lakehouse pattern on Databricks + Delta Lake + Unity Catalog + dbt-databricks. MIT-licensed, synthetic data only — banking risk-data engineering portfolio piece.", + "11_desc": "Serverless middleware enforcing responsible-AI compliance on LLM applications — PII detection, bias screening, hate-speech filtering, and RAG-powered policy enforcement on top of Azure OpenAI.", + "12_desc": "Cloud Carbon Intelligence platform estimating CO2e emissions from Azure infrastructure with AI-powered reduction recommendations. Clean Architecture, Azure AI Search semantic factor lookup, 88 automated tests. Built for EU CSRD Scope 3 compliance." }, "skills": { "label": "04 — SKILLS",