I am a Python AI Engineer and Full Stack Developer with over four years of professional software development experience. I build production-ready AI-powered applications using Python, TypeScript, Node.js, and modern web technologies.
I specialize in agentic AI systems, large language model workflows, Retrieval-Augmented Generation (RAG), prompt engineering, and multi-agent architectures. I have hands-on experience designing solutions with LangChain, LangGraph, Model Context Protocol-aligned tool interfaces, and LLM APIs.
I develop scalable backend services using FastAPI, Django, Node.js, Express.js, PostgreSQL, MongoDB, and RESTful APIs. I also build responsive frontend applications with React, Next.js, Redux Toolkit, Tailwind CSS, and real-time communication technologies.
I have delivered AI chatbots and automation workflows that improve operational efficiency. One of my healthcare strategy automation solutions reduced manual strategic brief creation time from 8–12 hours to under three minutes.
I am experienced in containerizing and deploying microservices using Docker and AWS services including EC2, S3, Lambda, and IAM. I focus on clean architecture, performant user experiences, SEO optimization, and reliable production deployments.
I enjoy solving complex product and engineering problems through practical AI implementations, scalable full-stack development, and well-designed distributed systems.
Built Retrieval-Augmented Generation pipelines using LangChain and Pinecone, including an LLM-powered chatbot integrated into product workflows.
Delivered full-stack applications with FastAPI and PostgreSQL backends alongside React.js and Next.js frontends. Designed, documented, and published RESTful APIs for business workflows and third-party integrations, and developed SEO-optimized client websites using TypeScript and Tailwind CSS.
Built an LLM API-powered chatbot that automated customer support across four product lines. Led end-to-end development of scalable, production-grade MERN web applications.
Improved frontend performance by 35% through lazy loading, code splitting, and memoization. Containerized applications with Docker and deployed services on AWS using EC2, S3, Lambda, and IAM.
Bachelor of Computer Applications (BCA), Computer Applications
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