I need an AI-driven matchmaking engine that instantly pairs customers posting aerial-service jobs with the most suitable drone pilots on my platform. The core task is to analyse each new job’s location and required time window, cross-reference it with every pilot’s real-time availability and base of operations, then surface the best match in milliseconds. Here is what I expect: • Input data: client job form (coordinates, date/time, brief description) and pilot profile fields (home base coordinates, service radius, availability calendar, skill tags). • Processing: calculate distance and travel feasibility, filter out pilots marked unavailable, rank remaining pilots by proximity and earliest availability. • Output: API endpoint that returns the top pilot (plus a short ranked list as secondary options) ready for immediate booking on the site. Please build the model, integrate it with our existing marketplace back-end (Node/Express + PostgreSQL), and document a simple REST endpoint so my devs can wire it to the front end. A lightweight microservice architecture is ideal; Python with FastAPI or a Node implementation is fine as long as response times stay under 500 ms. Acceptance criteria 1. Accuracy: at least 90 % of test bookings assign the nearest available pilot within the stated service radius. 2. Speed: matchmaking call < 0.5 s under a 1 000 concurrent-user load (we use AWS). 3. Clear README and Postman collection demonstrating the endpoint. Later on I may expand into automated support and market trend analytics, so please structure the code for future modules, but for now the single focus is flawless location- and availability-based matching.