I’m expanding an existing product and need a backend specialist who can wire in both Natural Language Processing and Predictive Analytics while adding a seamless Stripe checkout flow. The core goal is to process large volumes of user-generated data, run it through our AI models, store the results efficiently, and return responses in near-real time. Tech stack is flexible—Python (FastAPI), Node.js (Express) or a similar modern framework will work as long as you can demonstrate solid experience with AI libraries (e.g., TensorFlow, PyTorch, spaCy) and secure payment workflows via Stripe’s latest APIs. You’ll design or refine the data schema, implement scalable storage (PostgreSQL or MongoDB preferred), and expose clean REST or GraphQL endpoints that the frontend team can hit. Key deliverables • End-to-end Stripe integration covering tokenization, webhooks, subscriptions, and error handling • NLP pipeline that ingests text, performs intent classification and entity extraction, and logs results • Predictive analytics module (initially a time-series or classification model) deployable behind an API route • Robust data layer with migrations, indexing, and backup scripts • Postman or Swagger documentation plus a brief hand-off video Acceptance criteria 1. Payment attempts report correct status in Stripe dashboard and callbacks update our database without latency exceeding 500 ms. 2. NLP and predictive endpoints return results within 1 s for a standard payload and log to designated tables/collections. 3. All code passes linting and unit tests (minimum 85 % coverage) and ships in a Docker-ready repo. If this blend of AI integration and payment processing is in your wheelhouse, I’d love to see recent examples and hear how you’d architect the solution.