I build AI agents and backend systems intended to run in production, not just notebooks. My work focuses on the agent layer and the backend that powers it, including retrieval, tool-calling, cost and latency optimization, and reliable deployment. I have solid Java and object-oriented programming fundamentals.
I joined ASX today, as I posted on 2026-11-06 17:28 UTC.
I said I was looking forward to meeting folks on this platform to make meaningful connections.
I shared this as a personal update; the post does not explain what ASX refers to.
I made the post at 2026-11-06 17:28 UTC.
My headline is: AI/Agent Engineer • LLM, LangChain, LangGraph, MCP, RAG, FastAPI, AWS • Building production AI agents | B.Tech IT ’26
I worked as SDE Intern — AI/Backend Engineer at Listenloom (May 2025 to Aug 2025).
My education includes Manipal University Jaipur: Bachelor of Technology, Information Technology - Minor in Data Science (Aug 2022 to Jul 2026).
I completed CAMBRIDGE COURT: Higher Secondary (Class XII) — CBSE, Science (PCM) (2018 to 2022).
At Listenloom, I built an MCP server for conversational RAG and semantic search over historical meeting data: MCP server — conversational RAG / semantic search over 100+ hours of meeting data (embeddings + vector store + retrieval).
I developed and deployed a real-time Slack chatbot: Real-time AI Slack chatbot — meeting summaries & Q&A, used by 15+ teammates. It provided on-demand meeting summaries and LLM-driven Q&A, reducing the need for manual transcript review.
I improved LLM efficiency with token management and caching: LLM cost optimization — token management + caching, ~20% lower cost. This also improved response latency.
I also built a LangChain agentic workflow to extract and deduplicate action items from unstructured meeting transcripts and create Jira tasks automatically, cutting hours of manual data entry per week. I deployed FastAPI services on AWS EC2, containerized them with Docker, and worked on performance tuning and bug fixes to make responses faster and more reliable.
I am building AskOverlay — a Windows screen-overlay AI assistant: MCP-based screen-context layer · FastAPI backend · SSE token streaming · OAuth2 · Docker on AWS.
My project is AskOverlay, Present, May 2026, A desktop AI assistant that reads on-screen context and answers in a draggable overlay. → MCP-based screen-context layer feeding an LLM reasoning loop (Gemini) → FastAPI backend with SSE token streaming for real-time responses → OAuth2 auth, containerized with Docker, deployed on AWS → PySide6 desktop UI
My skills span AI agents and LLMs, LangChain and LangGraph, MCP, RAG, vector databases and semantic search; FastAPI, REST APIs and backend development; Python, Java, data structures, object-oriented programming and Git; machine learning with TensorFlow and PyTorch; and Docker, AWS, EC2, OAuth and PySide6. I am open to AI Engineer, LLM, Agent Developer and Backend roles as a 2026 graduate.