Building an AI-powered iOS app that helps professionals make better daily decisions about fueling, movement, recovery, and schedule - timed to their real-world context (calendar, biometrics, personal history), not generic advice.
The technical challenges: HealthKit data ingestion across multiple biometric signals, real-time context assembly for LLM reasoning, a predictive model that combines multiple physiological inputs to forecast the user's state forward, and a server-side pipeline that turns all of this into one actionable recommendation at the right moment.
Stack: Swift/SwiftUI, Supabase (Postgres + Auth + Edge Functions), Claude API. AI coding tools (Cursor, Claude) are core to how we build.
You'd be engineer #1. No legacy code, no inherited decisions. You shape the architecture from the first commit. Looking for someone who's built from zero before, is strong in Swift/SwiftUI, and comfortable owning the full stack including backend. HealthKit experience is a strong plus.