Parbhat Kapila
AI Full-Stack Developer
Building production AI systems with RAG, vector databases & LLMs. Available for full-time remote roles building production AI systems at startups.
About Me
I'm an AI Full-Stack Developer specializing in production-ready AI systems. Three years building and deploying applications that process 10,000+ documents, serve real users, and generate measurable business value. My expertise spans RAG architectures, vector databases, LLM integration, and full-stack SaaS development.
I architect AI systems that work at scale - from semantic search engines with sub-2s response times to intelligent document processing with 94%+ accuracy. My approach is production - first, ship fast, measure everything, iterate based on real user data. Whether it's building RAG pipelines, optimizing vector embeddings, or integrating payment infrastructure, I deliver systems that handle real traffic and real users.
Seeking opportunities with US/EU startups that are building AI-powered products. I thrive in fast-paced environments where execution matters more than perfect architecture. Ready to contribute from day one - my 600+ commits this year show consistent, daily progress toward shipped features. Let's build AI products that users actually love.
Skills & Tools
Key Achievements
Projects
Launched enterprise PDF intelligence platform processing 10,000+ documents at 94% accuracy in document classification and hierarchical summarization. Transforms 500-page documents into actionable insights in <2 seconds (previously took 4+ hours manually). Implemented hierarchical summarization with LangChain and GPT-4, semantic search using pgvector, and Razorpay for usage-based billing. Currently serving clients. Handles legal docs, financial reports, and research papers with 99.9% uptime in production.
Developed AI documentation system that turns any codebase into searchable knowledge. Auto-generates docs from 100,000+ lines of code with 92% relevance accuracy. Reduced developer onboarding from 2 weeks to 3 days (75% faster) for teams of 5+ developers. Implemented hybrid search combining vector similarity and BM25 keyword matching. Integrated OpenAI for intelligent code explanations. Currently processing 200+ repositories. Ships documentation updates in real-time as code changes.
Architected AI-powered email intelligence platform using RAG architecture for semantic search. Implemented distributed vector embeddings with pgvector and Redis clustering, achieving <200ms query latency at scale. Integrated Gmail API with OAuth, OpenAI for NLP processing, and PostgreSQL for persistent storage. Optimized embedding pipeline to handle 1000+ Emails. Reduced email search time by 80% through intelligent caching and query optimization. Serving daily active users with 99.9% uptime.
Experience
AI Full-Stack Developer | Product Builder
Independent Product Development
Architect and build production AI applications serving real users. Specialized in RAG architectures, vector databases (pgvector, Pinecone), and LLM integration with LangChain. Designed and deployed semantic search systems processing 10,000+ documents with sub-2s response times and 94%+ accuracy. Built full-stack SaaS platforms with payment infrastructure (Stripe/Razorpay/PayPal), PostgreSQL optimization, and automated CI/CD pipelines. Maintained 99.9% uptime across all production deployments. 600+ commits in 2025, shipping features daily. Technologies: React, Next.js, TypeScript, Python, Node.js, PostgreSQL, Redis, AWS, Docker.