About Me
GenAI / LLM Engineer (2026 B.E. Computer Science graduate) specializing in Retrieval-Augmented Generation, Agentic AI, and LLM-powered backend systems. Hands-on experience building production-style RAG pipelines, vector …
GenAI / LLM Engineer (2026 B.E. Computer Science graduate) specializing in Retrieval-Augmented Generation, Agentic AI, and LLM-powered backend systems. Hands-on experience building production-style RAG pipelines, vector search architectures, and context-aware multi-agent workflows using LangChain, FAISS, Chroma, and Weaviate. Strong foundation in Python, SQL, FastAPI, and prompt engineering
Experience
AI/ML Intern
Built and tested Retrieval-Augmented Generation (RAG) and Agentic AI workflows using dense embeddings and vector databases to ground LLM responses in domain-specific data. Benchmarked information retrieval methods (TF-IDF, cosine similarity, dense embeddings) to improve retrieval precision for downstream generation tasks. Developed context-aware AI pipelines with LangChain and open-source LLMs, integrating multi-step reasoning into agent workflows. Analyzed reasoning traces and information flow across agentic pipelines to identify and reduce hallucination-prone steps, improving response relevance.