Ranjeet S.

Most AI projects look impressive in a demo. The real challenge is making them reliable, scalable, and production-ready. I’m a Python AI Engineer and Backend Developer focused on building AI applications, LLM integrations, RAG systems, AI agents, conversational AI, data pipelines, APIs, automation, and scalable backend systems. I work with startups and businesses to turn AI ideas into production-ready products — from architecture and backend development to AI integration, data processing, testing, deployment, and ongoing improvements. What I work on ----------------- AI Agents, LLM applications & AI automation RAG, semantic search & vector databases Conversational AI & chatbots OpenAI, Claude, Gemini & LLM integrations AI-powered document processing Data pipelines, data processing & third-party integrations Python, FastAPI, Django & Flask applications REST APIs, WebSockets & backend services SaaS and data-driven applications Elasticsearch, PostgreSQL, MongoDB & Redis AWS, Docker, CI/CD & production deployment Core Technology -------------------- AI: OpenAI, Anthropic Claude, Gemini, LangChain, LangGraph, LlamaIndex, RAG, embeddings, vector search, function/tool calling, structured outputs, MCP and prompt engineering. Backend: Python, FastAPI, Django, Flask, Node.js, REST APIs, PostgreSQL, MongoDB, Elasticsearch, Redis, Celery, WebSockets and microservices. Cloud & Infrastructure: AWS, Docker, Linux, CI/CD, background workers, monitoring and production environments. Relevant Experience ----------------------- My experience spans AI applications, backend platforms and data-driven systems, including conversational AI, LLM integrations, AI document processing, SaaS products, API integrations, healthcare applications, risk management systems, CRM platforms and web data processing. I’ve also built data pipelines and backend workflows for processing, transforming and integrating data across applications and third-party systems, with a focus on reliability and automation. I focus on clean architecture, reliable integrations, proper testing and production-ready implementation — not just building something that works in a demo. If you have an AI, Python, data pipeline or backend project, share the requirements and I can help define the technical approach and implementation plan.