I’m a Software Engineer focused on building AI-powered applications, intelligent agents, backend systems, and production-ready software.
I enjoy working with Python, LLMs, RAG, APIs, and cloud technologies to turn ideas into practical solutions.
- 💻 Software Engineer with a B.Tech in Computer Science and Information Technology, experienced in Python, Java, and backend development.
- 🤖 Specializing in AI Agents and LLM-powered applications (LangGraph, LangChain, LlamaIndex, AutoGen).
- ⚙️ Experienced in building robust systems with FastAPI, WebSockets, GraphQL, and real-time communication.
- 🗄️ Proficient with MySQL, PostgreSQL, vector databases, and cloud deployments via Docker, AWS, and GCP.
- 📚 Contributed to research in Protein-Peptide Binding Prediction using deep learning (ICETCSE 2025).
Languages:
AI & Machine Learning:
Backend & Databases:
Cloud & DevOps:
- Designing and experimenting with multi-agent systems using LangGraph, LlamaIndex, and AutoGen.
- Developing agent workflows for intelligent task automation, tool calling, memory management, and LLM orchestration.
- Developed production software using Python, PySide6, and MySQL.
- Implemented robust multi-threaded application components with Socket, WebSocket, and GraphQL communication.
- Debugged and resolved critical issues utilizing Postman, Qt Designer, and VS Code.
- 🤖 Recruitment AI Agent: An LLM-powered recruitment platform using LangGraph, FastAPI, and PostgreSQL for intelligent task orchestration and document processing.
- 🏥 Medical RAG Chatbot: An advanced medical Q&A application built with Python, LangChain, and Vector Search, hosted on Hugging Face Spaces.
- 🎬 LLM Movie Recommendation System: An intelligent semantic understanding engine generating personalized recommendations using embeddings.
- 📊 Multi-Medical Diagnosis System (MMD): A prototype platform combining clinical report management, smart search, and FastAPI/Rust backends.
AI Agents
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LLM Orchestration
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RAG & Knowledge Retrieval
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Multi-Agent Systems
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Tool Calling & MCP
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Production AI Systems