I design and ship AI-powered systems — from LLM integrations and prompt-engineered pipelines to full-stack products with real users. I believe great AI engineering is 20% model choice and 80% systems thinking.
AI & ML: LLMs (OpenAI, Anthropic Claude, Gemini) · Prompt Engineering · RAG Pipelines · LangChain · Vector DBs (Supabase pgvector, Pinecone) · Agentic Systems
Backend: Python (FastAPI · Django) · Node.js · PostgreSQL · Supabase · REST APIs · Row Level Security
Frontend: React 18 · TypeScript · Vite · Tailwind CSS · shadcn-ui · PWA
DevOps & Infra: GitHub Actions · CI/CD Pipelines · Docker · Vercel · GitHub Pages
- An LLM-powered workout recommendation layer for FitForge using OpenAI function calling
- Exploring RAG pipelines and vector search for intelligent content retrieval
- Learning agentic AI architecture with LangChain and tool-use patterns
- Building production-ready AI features on top of existing full-stack apps
- Supabase auth, RLS policies, and serverless backend patterns
- Designing systems that make LLMs reliable and cost-efficient in real products
Open to AI Systems Engineering, Full-Stack AI, and ML Infrastructure roles.
Let's connect on LinkedIn →

