Software Engineer focused on deterministic systems, multi-agent architectures, and production-grade backend and AI systems.
I build systems where:
- Outputs are reproducible
- Failures are traceable
- Automation is controlled and reliable
- Design deterministic systems with clear execution guarantees
- Build structured multi-agent workflows (analysis → reasoning → action → validation)
- Develop backend and AI systems that are debuggable and production-ready
→ AI systems (LLM workflows, agent orchestration, evaluation)
→ Distributed systems + automation tooling
Actively contributing to:
- AI infrastructure (LLM tooling, agents, evaluation systems)
- Backend infrastructure and developer tooling
Approach: → consistent, high-frequency contributions → focus on real issues that get merged
- [Open] #6535 fix(ethereum): handle trace_filter traces missing result.output via c… in
graphprotocol/graph-node - [Open] #2331 fix(langgraph): handle null thread checkpoint in RemoteGraph.getState in
langchain-ai/langgraphjs - [Open] #5461 fix(converter): fall back on invalid JSON-like partial matches in
crewAIInc/crewAI - [Open] #5545 fix(flow,task): handle pydantic outputs in guardrail retries and checkpoint serialization in
crewAIInc/crewAI - [Open] #2316 fix(sdk): Backfill truncated history for regenerate branching in
langchain-ai/langgraphjs - [Open] #21386 fix(azureaisearch): preserve falsy metadata values in index mapping in
run-llama/llama_index - [Open] #21336 fix(elasticsearch): split sync and async store paths in
run-llama/llama_index
- Deterministic > unpredictable
- Evidence-based > assumption-driven
- Systems > scripts
- Debuggable > opaque
Languages: Python · TypeScript · JavaScript · Rust · Solidity
Core Areas:
- Backend systems
- AI systems (LLMs, agent workflows, evaluation)
- CI/CD tooling
- Distributed systems