I’m looking for an experienced AI automation developer to build a compliant production ready MLS based lead generation tool for my real estate wholesale business. Target Markets • Tucson • Phoenix • Atlanta and strong surrounding areas in Georgia Data Source Required • Licensed MLS API such as RESO Web API or approved real estate data provider • No scraping of Zillow Redfin Realtor or similar platforms What the System Must Do 1 Pull Active Listings Daily Filter for • Single Family Residences only • 150k to 400k price range adjustable per market • Year built 1950 to 2005 • 900 to 2500 sqft • Exclude new construction and luxury inventory 2 Apply Distress Filters must meet at least two • DOM over 45 days • One or more price reductions • Five percent or more total price drop • Keywords such as as is investor special fixer needs TLC cash only estate probate court ordered 3 AI Distress Scoring from 0 to 100 Score based on • Days on market • Price reduction behavior • Listing description language using NLP • Pricing versus area median Only export properties scoring 70 or higher 4 Automated Comp and MAO Analysis • Pull 90 day sold comps • 0.5 mile radius • Similar bed bath • Plus or minus 20 percent sqft Calculate • ARV using average price per sqft multiplied by subject sqft • Repair estimate 20 to 40 dollars per sqft based on condition • MAO equals ARV times 0.70 minus repairs minus 15000 assignment fee 5 Daily Output Google Sheet or CSV including • Address • List price • DOM • Price reduction percent • Distress score • ARV • Estimated repairs • MAO • Listing agent name and contact info The system must be scalable automated well documented and built with clean backend architecture such as Python with AI NLP integration. Experience with MLS APIs real estate data providers comp analysis and PropTech development is strongly preferred.