Python & AI engineer building reliable backend systems, agentic workflows, and developer tools.
I turn ambiguous product ideas into systems people can run, inspect, test, and maintain: APIs, persistence, integrations, evaluation loops, automation, and failure handling.
| Project | What it demonstrates |
|---|---|
| Food Journal AI Bot | Self-hosted Python/FastAPI/PostgreSQL service with LLM tool use, multi-channel input, idempotent webhooks, reliable delivery, and security-focused boundaries. |
| HeapHammer | Java/JVM performance engineering through deterministic Minecraft server workloads, retained-memory diagnostics, and reproducible regression reports. |
| LeetCode Coach Service | Python/FastAPI/SQLModel service with scheduled workflows, LLM coaching, migrations, a Telegram adapter, and a substantial automated test suite. |
| Skillweft | Node.js CLI for progressive disclosure, trusted capability selection, immutable skill snapshots, and explicit agent-host mutations. |
| Identify the Author | NLP experimentation with TF-IDF, classical models, calibration, cross-validation, and ensemble/submission tooling. |
| Value Sniper | Experimental Python quantitative-research dashboard for multi-signal analysis and historical backtesting, with limitations documented rather than hidden. |
Trinity Pilot explores typed desktop/browser automation with evidence checks and bounded retries. Scriptorium explores schema-gated editorial workflows and agent coordination. Squadron packages structured multi-agent delegation and state tracking through MCP.
Backend and AI engineering roles, product engineering, and focused automation work. If you need help turning an AI or workflow idea into a tested, maintainable system, connect with me on LinkedIn or email me.



