Title: AI Research Assistant Prototype using LangGraph / Python

We are looking for an AI engineer to build a lightweight proof-of-concept AI Research Assistant capable of performing structured document querying and multi-step reasoning workflows. This is NOT a production deployment project. The goal is to validate interaction flow, orchestration structure, and retrieval quality using a small local document set. Scope: • Build a simple AI assistant capable of: o ingesting a few PDFs/text documents, o answering contextual questions, o maintaining lightweight conversational memory, o performing multi-step reasoning or summarization workflows. Preferred Stack: • Python • LangChain or LangGraph • OpenAI API OR local model support • Simple UI (Streamlit, Gradio, or lightweight web interface) Requirements: • Clean modular structure • Runnable locally • No deployment required • No cloud infrastructure required • No database/server integration • Simple documentation included Deliverables: • Working local demo • Source code • Basic setup instructions • Short walkthrough video or screenshots Timeline: 2–3 days Budget: $120 Fixed Price Ideal Candidate: Experience with: • AI agents • RAG pipelines • LangChain/LangGraph • conversational AI workflows • lightweight orchestration systems Please include: • Similar AI workflow experience • Preferred stack • Estimated completion time