Python FastAPI Developer Needed - AI Chatbot Integration for Web Platform

I'm looking for an experienced Python developer with strong FastAPI skills to build and integrate an AI-powered chatbot into an existing web platform. The project involves designing a clean backend architecture, connecting to an LLM provider (such as OpenAI or Anthropic's Claude API), and making sure the chatbot interacts smoothly with the rest of the application's data and logic. This isn't a basic "wrap an API call" task — I need someone who understands how to properly structure a backend service around an AI integration: handling conversation context, managing requests efficiently, and building endpoints that are clean, reliable, and easy to extend later. What's involved: Backend (FastAPI): Design and build REST API endpoints using FastAPI to handle chatbot interactions — receiving user messages, managing conversation state/history, and returning AI-generated responses. The structure needs to be clean, well-organized, and built with scalability in mind (not a single bloated route handling everything). AI Integration: Connect the backend to an LLM API (OpenAI, Anthropic, or similar) and handle prompt construction, streaming responses (if needed), error handling, and rate limiting. Experience working with system prompts, context windows, and structuring conversations for consistent AI behavior is important here. Database/State Management: Store and manage conversation history and relevant context so the chatbot maintains continuity across a session (and ideally across sessions, depending on the use case). Experience with PostgreSQL or another database for this kind of structured, relational data is a plus. Requirements: • Strong experience with Python and FastAPI specifically (not just Flask/Django) • Hands-on experience integrating LLM APIs (OpenAI, Anthropic, or similar) into a backend service • Understanding of async programming in Python (FastAPI is async-first) • Experience with structuring and managing conversation context for chatbots • Comfortable with database integration (PostgreSQL preferred) for storing chat history/state • Clean coding practices and ability to document what was built Ideal candidate: Someone who has built or worked on AI chatbot backends before — not just called an API once, but actually handled the architecture around it: context management, error handling, and making the system reliable in production.