Java Backend Engineer (Entry-Level)
Focused on Distributed Systems, High-throughput Backend, and AI Agents
I am interested in building reliable, scalable backend systems, and exploring how LLMs & Agent architectures can be applied to real engineering scenarios.
Backend & Infrastructure
AI & Engineering
Kafka · Spring Boot · Stream Processing
- Designed a high-throughput chat message ingestion pipeline using Kafka
- Modeled structured messages for real-time sentiment analysis
- Generated alerts based on sentiment trends and configurable thresholds
- Focused on throughput, data modeling, and real-time processing
Keywords: Kafka, Producer design, Stream processing, system scalability
LangChain4j · LLM · Tool Calling
- Built an AI Agent to evaluate and improve generated code
- Combined rule-based checks with LLM reasoning
- Designed extensible tool interfaces for future RAG and metrics integration
- Emphasized agent architecture and evaluation logic
Keywords: AI Agent, Tool Calling, LLM evaluation, extensibility
- AI Agent architecture & evaluation strategies
- Kafka-based high-concurrency backend systems
- Multi-level caching design (Caffeine + Redis)
- Backend engineering best practices & observability
- GitHub: https://github.com/Zewang0217
- Blog / Notes: (to be added)
- Resume: Available upon request
Open to Backend / Platform / AI-related opportunities.