About
Experienced in building backend APIs and AI-powered projects, with interests in backend engineering, Generative AI, and scalable systems.
Skills
Selected work
A mix of backend APIs, AI projects, and frontend apps built to solve practical problems.
Developed a production-ready Retrieval-Augmented Generation (RAG) platform that analyzes GitHub repositories by indexing README files into Redis vector search and enabling AI-powered conversations with source-grounded responses. Engineered an optimized embedding pipeline using Google Gemini REST API with SHA-based caching, batch embedding, recursive text chunking, and cosine similarity search to reduce re-indexing latency and API overhead. Built scalable FastAPI APIs with PostgreSQL persistence, containerized the application using Docker, and optimized cloud deployment with background task processing and dynamic Redis index management.
Designed a conditional Retrieval-Augmented Generation (RAG) workflow using LangGraph that intelligently routes user queries to either direct LLM inference or document retrieval based on query intent. Built a semantic retrieval pipeline by processing PDF documents into vector embeddings, indexing them with FAISS, and retrieving relevant context using LangChain for grounded response generation. Developed an interactive Streamlit application integrated with Groq LLM to deliver low-latency, context-aware responses with modular workflow orchestration for extensibility.
Built a full-stack second brain application to save, organize, and share YouTube links, tweets, and notes. Developed a FastAPI backend with JWT authentication, REST APIs, MongoDB integration, and CRUD functionality. Implemented responsive frontend using React and TypeScript with dynamic content rendering and API integration. Deployed frontend on Vercel and backend on Render with environment variable management and production configuration. Configured CORS handling, API communication, and cloud database connectivity using MongoDB Atlas.
Built a multi-agent AI research pipeline using LangChain and LangGraph for automated web research workflows. Implemented agent orchestration with specialized search, scraping, writing, and critique agents. Integrated Tavily web search and custom web scraping tools using BeautifulSoup and Requests. Developed structured research report generation with critique and feedback loops for iterative refinement.
Work Experience
Get in Touch
I'm open to backend, AI, and product engineering opportunities. Reach out by email or connect on LinkedIn. Send me an email or message me on LinkedIn .


