AI Engineer · LLM Integration & Automation · Full-Stack Systems
I build production AI systems — LLM agents, RAG pipelines, MCP servers, and automation workflows — backed by 25+ years of hands-on engineering. I architect the full stack from model integration to deployment, and self-host everything on my own infrastructure.
Currently shipping AI-augmented trading systems at Verified Investing (TypeScript, Next.js, React Native, real-time data pipelines).
🤖 AI Agent Systems — Production agent workflows with multi-model orchestration (OpenAI, Claude, Gemini), tool calling, persistent memory, and structured outputs. 50+ deployed systems handling financial analysis, content synthesis, and data pipelines.
🔍 RAG Pipelines — End-to-end retrieval-augmented generation: ingestion, embeddings (OpenAI), vector search (Supabase/pgvector), and conversational agents with hybrid retrieval + web augmentation.
🔌 MCP Servers — Model Context Protocol integrations that expose real-world APIs to LLM agents. Dual-protocol (MCP + REST), Docker-based, stateless, production-ready.
⚙️ Infrastructure — Self-hosted on Coolify/Hetzner. Docker, CI/CD, Postgres, Supabase, n8n, Linux. I own the full pipeline.
| Project | Description |
|---|---|
| monarch-money-mcp | MCP server exposing personal finance data to LLM agents. Python, FastMCP, Docker. |
| privacy-mcp | MCP server for Privacy.com virtual card management via AI agents. Python, FastMCP, Docker. |
| ai-stock-analysis-engine | Automated financial analysis: parallel technical indicators + GPT-4o sentiment + HTML reports. |
| openwebui-chat-backend | Async chat middleware bridging Open WebUI to custom AI agent pipelines with full observability. |
| youtube-rag-knowledge-base | Ingest YouTube channels → Gemini transcription → embeddings → pgvector → conversational RAG agent. |
| daily-ai-news-brief | Automated daily intelligence: RSS ingestion → Perplexity research → AI synthesis → email. Running in production. |
AI/LLM: OpenAI · Claude · Gemini · LangChain · RAG · MCP · Agent Orchestration · Embeddings
Languages: TypeScript · Python · JavaScript
Backend: Next.js · Hono · FastMCP · Starlette · PostgreSQL · Supabase · pgvector · Redis
Frontend: React · React Native · Tailwind CSS
Infrastructure: Docker · GitHub Actions · Coolify · Hetzner · Linux · Nginx · CI/CD
Automation: n8n (50+ workflows) · Python scripting · Webhook pipelines