Aashutosh Kumar Bhardwaj

I’m an AI/ML engineer with hands-on experience building LLM-powered applications, Retrieval-Augmented Generation (RAG) systems, and agentic AI workflows. I work with LangChain and LangGraph to turn ideas into working AI features that users can rely on.

I combine Python backend development with prompt engineering, vector search, and LLM API integration. I focus on retrieval quality and contextual reasoning—so my applications can interpret queries accurately and deliver actionable results.

I’ve contributed consistently to open source as a Maintainer & Project Admin (GSSoc) and as an Open Source Contributor (GirlScript Summer of Code). I led development and maintenance of project features, reviewed pull requests, managed issues, and supported contributors by improving code quality and scalability.

In projects, I built an AI Database Performance Advisor using RAG with FAISS/Chroma and LLM APIs, and an AI Finance Assistant (Gullak AI) with 500+ downloads. I also developed DeepSeaDNA AI—National Marine Data Platform (MoES)—processing 1M+ records/day, optimizing queries to achieve <200ms latency under load, and enabling reliable access for 500+ users.