Senior AI Engineer Needed to Build Production-Ready RAG Chatbot & AI Agent Workflow

We are looking for a highly skilled Senior AI Engineer to help us design and build a production-ready AI chatbot and agent workflow using modern LLM, RAG, and automation technologies. The goal is to create an intelligent assistant that can understand business documents, retrieve accurate information, answer user questions, and perform basic automated actions through an API-based workflow. This is not just a simple chatbot. We need someone who understands AI architecture, retrieval quality, prompt engineering, vector databases, scalable backend design, and how to structure the solution for future production use. The ideal freelancer should be able to take a business use case, recommend the right AI architecture, build the core system, and document everything clearly. *Scope of Work:* •⁠ ⁠Design the AI solution architecture for a RAG-based assistant •⁠ ⁠Build a document ingestion and processing pipeline •⁠ ⁠Implement vector search and retrieval logic •⁠ ⁠Integrate an LLM such as OpenAI, Claude, Gemini, Mistral, or similar •⁠ ⁠Build chatbot/API functionality for user questions •⁠ ⁠Add prompt engineering and response-quality improvements •⁠ ⁠Create a basic AI agent workflow for simple task automation •⁠ ⁠Ensure the solution is modular, secure, and scalable •⁠ ⁠Provide deployment guidance and technical documentation •⁠ ⁠Recommend next steps for production rollout *Required Skills:* •⁠ ⁠Generative AI and LLM development •⁠ ⁠RAG chatbot development •⁠ ⁠AI agent / agentic workflow development •⁠ ⁠LangChain, LangGraph, LlamaIndex, or similar frameworks •⁠ ⁠Python, FastAPI, REST APIs •⁠ ⁠Vector databases such as Pinecone, Chroma, Weaviate, FAISS, or similar •⁠ ⁠Prompt engineering and retrieval optimization •⁠ ⁠Cloud deployment knowledge on AWS, Azure, or GCP •⁠ ⁠MLOps / LLMOps experience is a strong plus *Deliverables:* •⁠ ⁠Working RAG chatbot prototype •⁠ ⁠Document ingestion and retrieval pipeline •⁠ ⁠LLM integration •⁠ ⁠Simple API or chatbot interface •⁠ ⁠Basic AI agent workflow •⁠ ⁠Clean source code •⁠ ⁠Setup instructions and documentation •⁠ ⁠Recommendations for scaling the system *Ideal Candidate:* We are looking for someone who has already built real AI systems, not just demos. Experience with enterprise RAG, AI agents, automation, chatbots, document intelligence, or production-grade AI applications will be highly preferred. This can start as an initial milestone, but we are looking for a long-term AI engineering partner if the first phase goes well. Please include examples of similar RAG systems, AI agents, chatbots, or LLM-based applications you have built.