We are hiring an AI developer to help build the core logic for Fitness Lab AI, a behavior-first fitness app that delivers personalized coaching through emotional intelligence and biometric feedback. The scope includes: Design and implement an AI-driven system using GPT (via OpenAI API) or a custom lightweight LLM to generate adaptive fitness plans based on user mood, stress, and biometric data. Create a micro-coaching engine that uses contextual inputs (e.g., "I feel anxious today") to deliver emotionally intelligent guidance using natural language generation. Build feedback loops where user input (via chat or buttons) dynamically adjusts recommendations and daily goals. Integrate with wearable APIs (e.g., Apple Health, Google Fit, or Fitbit) to ingest biometric data like sleep, heart rate variability, and activity level. Develop lightweight backend logic (Firebase or Supabase preferred) to store user state, plan history, and feedback. Ensure all AI logic is modular, well-documented, and ready for iteration and testing. Deliverables: GPT/LLM-powered personalization engine (text-based coaching + plan adaptation) API integration with at least one biometric data source Initial backend setup and endpoints for chat, feedback, and plan generation Developer documentation for future iteration and testing