Freelance AI Engineer Needed – Build an AI-Powered Real Estate Listing Monitor

I buy distressed residential properties in the midwest USA and want to automate the process of finding new opportunities. The goal is to build a system that continuously monitors new residential listings, uses AI to analyze listing photos and descriptions, identifies properties that appear distressed, and immediately notifies me with the listing details. This is intended to become the foundation of a much larger AI acquisitions platform, so I'm looking for someone who values clean architecture and scalable design. What the System Should Do Continuously monitor newly listed residential properties. Analyze listing photos using an AI vision model to determine whether a property appears distressed. Analyze listing descriptions for phrases and language commonly associated with distressed properties (such as "investor special," "fixer upper," "TLC," "cash only," etc.). Flag a property if either the photos or the description indicate distress. Send an immediate notification (SMS or email) that includes: property address, listing price, listing agent name, agent phone number, agent email, brokerage, link to the listing, and a brief explanation of why the AI flagged the property. The target is to receive notifications within approximately five minutes of a qualifying listing becoming available. Preferred Technology I'm open to recommendations, but I expect the solution to involve technologies such as Python, OpenAI or Google Gemini vision models, APIs for listing data (MLS, RESO, IDX, or another reliable and compliant source), Docker, Git, Twilio or another SMS provider, and PostgreSQL or another appropriate database. The most important factor is building a reliable, maintainable system, not using a specific technology. I do not require MLS access. I'm flexible on the listing data source and open to Zillow, Realtor.com, RapidAPI-based listing feeds, or any other approach the developer recommends, as long as it's reliable and the developer is upfront about any terms-of-service or data-reliability tradeoffs of the chosen source. What I'm Looking For Experience with Python development, AI integrations, computer vision, API development and integrations, automation, cloud deployment, and building production-ready applications. Experience with real estate data, MLS/IDX/RESO feeds, or property technology is a significant plus. Deliverables Clean, well-organized source code; documentation for setup and deployment; configuration files; error handling and logging; a system that can run continuously with minimal maintenance; and instructions for future expansion. Timeline I'd like to have a working Version 1 as quickly as possible, ideally within the next few weeks. When You Apply Please include examples of AI or automation projects you've built, any experience with computer vision or image analysis, any experience with real estate APIs or MLS/IDX/RESO data, your recommended technical approach for this project, your estimated timeline and budget, and any questions or concerns you have about the project. I'm looking for someone interested in building a long-term relationship. If Version 1 is successful, I have additional AI automation projects planned and would prefer to continue working with the same developer. Definition of Done (Critical Requirement) This project is not considered complete when code is written or when a prototype is demonstrated. The final deliverable must be a fully functional, deployed Version 1 system that is actively running and automatically performing its intended purpose. When the project is delivered, I expect to be able to immediately begin receiving qualified property alerts without needing to complete additional technical setup, coding, configuration, integrations, or development work. The completed system must: be deployed and running continuously (24/7); automatically monitor the agreed-upon listing data source; automatically analyze new listings using AI; automatically identify properties matching the distress criteria; automatically send notifications to me without manual intervention; continue operating after delivery without requiring the developer to manually run scripts or restart processes; include all required API connections, accounts, credentials, and integrations necessary for operation; and include documentation explaining how the system operates and how to maintain it. A successful delivery means: "I wake up tomorrow, a distressed property is listed that matches my criteria, and the system automatically sends me the alert." That is the acceptance criteria. Deployment Responsibility The developer is responsible for setting up the hosting environment, configuring APIs, connecting all required services, setting up notifications, testing the complete workflow from listing detection to notification delivery, and confirming that the system runs automatically without my involvement. I am not looking for a tutorial, a code repository, or a partially completed application. I am looking for a working AI-powered monitoring system.