AI-Driven RAG Chatbot & Test Automation

# AI Platform – RAG Chatbot + AI Test Automation Looking for an experienced **AI/Python developer** to build an MVP consisting of two related AI modules: ### 1. RAG Chatbot Build a secure chatbot that can answer questions using uploaded/internal knowledge. Key expectations: - Upload and process **PDF, DOCX, text and other documents** - Document chunking, embeddings, vector search & retrieval - Source-grounded answers with **citations/references** - Conversation history, context & memory management - Guardrails, hallucination control and prompt-injection protection - RAG evaluation: **relevance, groundedness/faithfulness, retrieval quality, hallucination, etc.** - Support multiple LLM providers/models - Token usage & **cost tracking** ### 2. AI Test Generation & Automation Core flow: **PRD / BDD / PDF / Text / Jira → RAG → AI Test Cases → Review → Excel → Playwright → Execution → Dashboard** Key expectations: - Generate structured manual test cases with **requirement traceability** - Review/edit and export test cases to **Excel** - Generate **Playwright automation** - Controlled test execution - Pass/Fail/Skipped results - Current + **historical dashboards**, trends and coverage ### Shared AI / Platform Capabilities The architecture should support: - **Multi-agent orchestration** – Planner, Generator, Executor, Evaluator, etc. - Agent/tool communication and **MCP integration** where appropriate - RAG & context management - Memory & caching - AI evaluations - Guardrails & security - LLM/model abstraction - Logging & observability - Retry/error/timeout handling - **Infinite-loop protection** - Token/context/cost dashboard - Authentication & secure document handling - Docker/cloud deployment Likely technologies: **Python, FastAPI, React/Next.js, Playwright, PostgreSQL/pgvector, Docker, MCP, OpenAI/Anthropic/Gemini, DeepEval/RAGAS**, or suitable alternatives. ### When Applying Please provide: - Relevant **RAG / Agentic AI / Playwright / LLM evaluation** experience - Examples/links to similar projects - Proposed architecture & technology stack - What you would build vs. use off-the-shelf - **Milestone-wise timeline & cost** - Expected hosting/LLM running costs We prefer **simple, practical and extensible architecture over unnecessary complexity**. Please start your proposal with **“AI-QE-RAG”** so we know you've read the requirement.