🚀 AI Engineer focused on building LLM agents and RAG systems that can be shipped to production.
I work end-to-end: from backend APIs to web interfaces, with a strong focus on clean code, scalability, and observability.
- LLM agents with LangChain and LangGraph (multi-agent architectures)
- RAG pipelines with vector databases (Milvus, Qdrant)
- Backend in Python / FastAPI
- Web UIs in React
- Monitoring via structured logging + dashboards
MinecraftButlerAI - LangGraph agent with RAG, voice input (faster-whisper), and Redis conversation memory, served as a FastAPI backend for a Minecraft mod. Full Docker Compose setup.
- Building production-grade agentic systems (WhatsApp / Microsoft Teams / Web)
- Improving RAG quality (chunking, embeddings, retrieval, evaluation)
- Hardening deployments and observability