Build a Basic Python RAG Chatbot Prototype

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I am looking for a Python developer with experience in AI and Retrieval-Augmented Generation to create a simple proof-of-concept chatbot that can answer questions from a small set of internal documents. The prototype should load a few sample SOPs, policy documents, or training guides, convert the content into embeddings, retrieve relevant sections, and generate answers using an LLM API. Must be built in Python, and should integrate with our existing Postgres database. Experience with vector databases (like pgvector or Pinecone) and LLM APIs (OpenAI or Claude) is required.

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