React Native / Expo Native Foundation Engineer for Fitness App Timers, Audio, and Notifications

I’m building a mobile fitness app with complex workout execution, including background timers, continuous audio cues, and occasional video capture. I’m looking for an experienced React Native + Expo developer to set up and guide the core mobile architecture. This role is *not* about building the full product from scratch. It’s about creating a *robust native-capable foundation* that supports fast iteration and collaboration with AI tools (Claude Code) for feature development. The first milestone is not a full app; it is a native-capable proof of concept showing that timers, audio cues, notifications, and state restoration work correctly on real iOS and Android devices with the screen locked and the app backgrounded. What you’ll be responsible for -Setting up a React Native (TypeScript) app using Expo Development Builds (EAS) — not Expo Go -Creating a reliable background-safe timer system (timestamp-based timer restoration plus native notifications/audio/foreground-service strategy) -Implementing audio cue engine that supports metronome/cadence/counting, background playback, ducking/mixing, and interruptions (spoken cadence / metronome) -Configuring local notifications that fire when the app is backgrounded or the screen is off -Implementing basic camera/video capture (short clips, local storage) -Advising on platform differences (Android vs iOS) and best practices -Reviewing and integrating AI-generated code (Claude Code) into a clean codebase -Real-device testing on iOS and Android Key technical requirements -Proven experience shipping React Native apps to production -Strong knowledge of Expo beyond Expo Go (EAS, dev builds, native config) -Experience with: --Background timers / alarms --Local notifications --Audio playback that continues with the screen off -Understanding of Android foreground services and iOS background constraints -Comfortable working with GitHub and incremental feature branches Nice to have -Experience collaborating with AI-assisted coding tools (knowing where common pitfalls may be and advising accordingly) -Clear communicator who can explain trade-offs and limitations Project structure -You’ll start by building a “native-capable harness”: --Timer proof --Notification proof --Continuous cadence audio proof --Camera proof -Once the foundation is solid, the project will scale via AI-assisted feature development and additional engineers.