AI-Powered Full-Stack Build

I’m spinning up a production-grade application that delivers AI-driven recommendations to end users. The heart of the project is a performant micro-service written in Python/FastAPI that calls LLM chains (LangChain or LangGraph) and returns results to a React web client backed by PostgreSQL. Performance is my top architectural priority, so every layer—from data model to API to front-end rendering—must be tuned for speed and low latency.

Here’s the technology mix the codebase already leans on, so you’ll need to be fluent in all of it:

• Python 3.x with FastAPI
• React (modern hooks, TypeScript a plus)
• PostgreSQL (schema design, query optimisation)
• LangChain or LangGraph for LLM orchestration
• AWS or Azure for deployment, monitoring and CI/CD
• Solid system-design skills around caching, load balancing and horizontal scaling
• Previous hands-on experience shipping AI/LLM-powered features into production

You’ll take ownership of architecture decisions, implement the recommendation pipeline, wire up the front end, write tests, containerise everything, and push a first release behind feature flags. Five or more years in full-stack roles will let you hit the ground running.

RIYOB is a Talent Acquisiton Agency which will introduce you to my team and connect to client and work will take place under our supervision; once green-lit, you’ll collaborate with their product manager and designer, pushing code to their GitHub and demoing progress in weekly stand-ups. I value clear communication, clean commits, and pragmatic solutions over theoretical perfection—so if you can show working software quickly and iterate, we’ll get along well.

Please share links to two or three live projects (or public repos) where you built or significantly contributed to a similar AI or GenAI feature set, along with a brief note on the performance wins you achieved.

Note:- We're in a startup phase and getting new freelancers join our network and accomplish the clients project.