I build backend-driven AI systems with a focus on LLM applications, retrieval systems, and agentic workflows. My work combines Python backend engineering with APIs, databases, data pipelines, retrieval, model integration, evaluation, and deployment.
I’m particularly interested in the systems behind reliable AI applications, including LLM inference, retrieval quality, performance, scalability, and the engineering challenges involved in building them.
Currently strengthening my systems foundations, exploring applied AI research, building beyond tutorials, and working toward open-source contributions.
Python • Java • C • C++ • SQL
PyTorch • Transformers • scikit-learn • NumPy • Pandas
LLM APIs • RAG • Embeddings • Semantic Search • Vector Retrieval • LangGraph • AI Agents • Tool Calling
FastAPI • REST APIs • Pydantic • SQLAlchemy • Uvicorn
PostgreSQL • Redis
Docker • Linux • Git • GitHub
- AI Systems
- LLM Applications
- Retrieval Systems
- Agentic AI
- Inference Engineering
- Applied AI Research
- Open Source
