Open to opportunities

Pranjal Sinha

@pranjalsinha1

I build full-stack web applications, RAG pipelines, and multi-agent AI workflows using Python, React, FastAPI, and LangChain.

India

Message

What I'm looking for

I'm looking to build scalable web applications, RAG pipelines, and agentic AI systems while contributing to open-source collaboration and growing through hands-on cloud and GenAI work.

I've built a multi-agent AI research assistant that coordinates planning, information collection, fact checking, synthesis, citation generation, and report writing with LangGraph and LangChain.

I created its FastAPI and React.js application, integrated Web Search, Wikipedia, and arXiv APIs, and used LangSmith to trace and debug LLM workflows. I deployed the backend on Render and the frontend on Vercel.

I've also built a RAG-based YouTube Video Q&A system with transcript extraction, embeddings, and semantic search, plus a fully responsive Netflix clone. I'm an active GSSoC open-source contributor and a Google Developer Group member.

Experience

Work history, roles, and key accomplishments

AI-Powered YouTube Video Q&A System (RAG)

Self Employed

Developed a RAG-based application where users can ask questions from any YouTube video using the video URL. Built React frontend and FastAPI backend with LangChain-based retrieval pipeline, implementing transcript extraction, embeddings generation, and semantic search for accurate contextual answers.

RAG React fastAPI Lang Chain Transcript Extraction Embeddings Semantic Search

Multi-Agent AI Research Assistant

Self Employed

Developed a multi-agent AI research assistant using LangGraph and LangChain, orchestrating specialized agents for planning, information collection, fact checking, knowledge synthesis, citation generation, and report writing. Integrated Web Search, Wikipedia, and arXiv APIs as research tools to collect web and academic information and generate source-aware research reports.