AI Backend Developer (FastAPI + LangGraph + RAG + PostgreSQL + Celery)

We are building an AI-powered career guidance platform that helps students and professionals with career discovery, resume generation, AI career coaching, personalized learning roadmaps, and intelligent job matching. We're looking for an experienced backend developer with strong AI integration experience to help build and improve our production backend. The ideal candidate has experience building scalable AI applications using FastAPI, LangGraph/LangChain, PostgreSQL, vector databases, background workers, and cloud deployment. This is a long-term project with multiple phases. Current Stack FastAPI (Python 3.12) PostgreSQL + pgvector SQLAlchemy Async Alembic Celery + Redis LangGraph LangChain OpenAI HuggingFace Embeddings JWT Authentication Google & GitHub OAuth Supabase Storage Azure Container Apps Docker GitHub Actions Responsibilities Build new FastAPI endpoints Design scalable backend architecture Implement AI workflows using LangGraph Improve our RAG pipeline Optimize pgvector search performance Integrate OpenAI APIs Build asynchronous background workers using Celery Implement secure authentication (JWT, OAuth, MFA) Work with PostgreSQL and SQLAlchemy Improve API performance and reliability Write clean, maintainable code Participate in architecture discussions Nice to Have Experience with: MCP (Model Context Protocol) AI Agents n8n Voice AI Vapi Redis Supabase Azure Sentry Prometheus Required Skills Python FastAPI PostgreSQL SQLAlchemy Celery Redis Docker Git REST APIs WebSockets OpenAI API LangChain LangGraph Vector Databases JWT Authentication Deliverables The selected developer will help us with: AI Chat improvements Resume generation pipeline Career recommendation engine Learning roadmap generation Vector search optimization Authentication enhancements Background task improvements Deployment and production support Preferred Experience Please include examples of projects involving: AI agents RAG applications LangGraph FastAPI LLM integrations Production AI systems To Apply Please answer the following: Have you built production AI applications using FastAPI? Have you worked with LangGraph or LangChain? Have you implemented RAG with pgvector or another vector database? What LLM providers have you integrated? Please share links to relevant GitHub repositories or portfolio projects. What is your availability over the next few weeks?