I’ve always been naturally curious. I can’t stop asking why, how, and what about the inner workings of things. This habit pushed me toward first-principles thinking, where I break problems down to their roots instead of just patching symptoms.

That same curiosity is what led me into AI engineering, and it’s why I love building systems that actually work in the real world. I create reliable RAG pipelines that handle messy customer queries, agentic workflows that move smoothly from idea to production, and LLM-powered applications that teams can trust.

What sets me apart is how I approach problems. I don’t just implement code. I dig deep to understand why something works, where it usually breaks under pressure, and how to make it faster, cheaper, and more robust. This first-principles mindset helps me solve the hard, ambiguous challenges that stop most projects.

These days I work across the full stack: designing custom RAG assistants for real customer use cases, automating multi-stage content pipelines with n8n, Claude Code, and Gemini API, and shipping solid production systems using LangChain, ChromaDB, and FastAPI.

I’m an active open-source contributor, I pick up new tools and ideas quickly, and I genuinely care about building things the right way.

If you’re working on AI products, especially production RAG systems, agents, or LLM applications, and you need someone who thinks deeply, enjoys the tough parts, and consistently delivers systems that hold up, I’d love to connect and talk.