RAG-Based Internal AI Chatbot Developer (OpenAI API)

We are looking for an experienced developer to build an internal AI chatbot using a Retrieval-Augmented Generation (RAG) system powered by the OpenAI API. Project Overview The system will allow admins to upload and manage internal documents (PDF, DOCX, TXT, etc.), which will be used as a secure knowledge base. Internal users will interact with a Chatwoot-style chat interface to ask questions, and the chatbot must generate responses strictly grounded in the uploaded documents. Key Responsibilities Develop a RAG-based chatbot using OpenAI API Build an admin panel for document upload and management Implement document processing (parsing, cleaning, chunking, embeddings) Integrate a vector database for semantic search and retrieval Develop an internal Chatwoot-like chat interface Ensure all responses are strictly based on uploaded/internal documents Implement role-based access control (Admin / Internal Users) Required Skills Strong experience with OpenAI API (Chat + Embeddings) Hands-on experience building RAG-based systems Experience with vector databases (Pinecone / Weaviate / Chroma / FAISS) Backend development experience (Node.js / Python / TypeScript) Experience with document processing pipelines and embeddings Timeline Maximum: 1 Week Important Note Proposal must start with “WAW” Timeline and cost must be clearly mentioned in the proposal AI-generated or template-based proposals will be rejected