Description
Summary We’re looking for a Python Full-Stack Developer to build a LangGraph-based AI customer support agent. The agent will help answer customer questions using information from our internal documents and knowledge base. It should understand user intent, maintain conversation context, retrieve accurate information through a RAG pipeline, and escalate complex or sensitive queries to a human support representative when required. The project will include both backend development and a simple frontend chat interface. The backend should be built in Python and handle the LangGraph workflow, document retrieval, conversation memory, API integrations, error handling, and logging. The ideal developer should have experience with: Python and backend API development LangGraph and LangChain RAG pipelines, embeddings, and vector databases OpenAI or Claude API integration PostgreSQL, Supabase, Pinecone, or pgvector React, Next.js, or another frontend framework Third-party API and customer support integrations Conversation memory, tool calling, and human handoff workflows The final solution should be reliable, easy to maintain, and designed for real customer support operations rather than being a basic chatbot demo. Please include examples of similar LangGraph, RAG, AI-agent, or customer support automation projects you have completed. Also briefly explain the technology stack you used and your role in the project.