I’m building a web application that uses AI-based image generation as part of a creative workflow. The app is currently fully functional as a prototype, built using Emergent but now needs to be made production-ready with a secure backend and scalable infrastructure. You’ll work on setting up the technical foundation that allows the app to support 1,000+ users and hundreds of AI requests per minute, with a strong focus on speed, reliability, and data protection. ⸻ Scope of Work • Build a secure backend (Node.js / Python) with user authentication (Supabase Auth or Firebase Auth). • Set up a database (Supabase / PostgreSQL) for user data and job tracking with Row Level Security (RLS). • Implement a background job queue (Redis + BullMQ / Cloud Tasks) to handle multiple concurrent AI generation requests efficiently. • Connect to existing AI APIs through the backend with proper rate limiting, retries, and error handling. • Deploy the backend on Fly.io / Render / Cloud Run with autoscaling to handle load spikes. • Add logging, monitoring, and daily backups. • Protect sensitive logic and data (handled server-side only, never exposed to users). ⸻ Preferred Tech Stack • Backend: Node.js (Express/NestJS) or Python (FastAPI) • Database: Supabase (PostgreSQL) • Auth: Supabase Auth / Firebase Auth • Queue: Redis (BullMQ or similar) • Hosting: Fly.io / Render / Cloud Run • AI Integration: Any major AI API • Monitoring: Sentry / Logtail / Uptime Robot ⸻ You Should Have Experience In: Designing scalable APIs that process AI workloads -Managing queues and background jobs (Redis / BullMQ / Celery) -Implementing secure authentication and data isolation (RLS, JWT) -Working with AI APIs and asynchronous processing - Deploying autoscaled apps on cloud platforms -Writing clean, well-documented code with good error handling ⸻ Timeline • Phase 1 (2–3 weeks): Backend setup, job queue, API integration, and deployment • Phase 2 (1–2 weeks): Security layer (encryption, rate limits, backups) and load testing