Job Description: I’m looking for an experienced AI / backend engineer to build a document intelligence system for commercial real estate LOIs stored in Google Drive. Phase 1 (Prototype): 1. Automatically extract key deal terms (rent, term, TI, options, major clauses, dates, parties, etc.) into a structured database 2. Store and index the original document text 3. Build a chat-style interface where I can ask questions about the deals and receive answers with citations to the source documents This should combine structured data extraction (JSON/schema-based) with a retrieval-based AI system (RAG) for clause-level Q&A. Phase 2 (Expansion): • Dashboard to compare deal terms across LOIs (rent, TI, term, etc.) • Version tracking of LOIs (redlines / updated drafts) • Slack integration to interact with the AI directly from Slack Requirements: • Experience building LLM-powered document extraction systems • Strong Python and backend development skills • Experience with RAG / vector databases • Experience designing structured schemas from legal or contract documents • Ability to build a clean, production-ready pipeline • Experience with PDF parsing / OCR a plus • Real estate or legal tech experience is a bonus I’d like to start with a small prototype (10–20 LOIs) and expand into Phase 2 if successful. Please include examples of similar document intelligence or contract extraction systems you’ve built.