Senior Kotlin Multiplatform Engineer - YOnC SDK

Yo is building an AI inference platform that runs directly on smartphones - turning the phone in your pocket into part of a global AI network. The mobile SDK that ships this to Android and iOS devices is moving to a shared core built in Kotlin Multiplatform, replacing what was previously two separate native codebases. This is a foundational hire on a KMP effort that is just getting started. You will help build the shared core from the ground up and shape its public API alongside the existing Android and iOS engineers. Key Responsibilities Build and maintain the KMP shared core: business logic, state machines, and data models used by both the Android and iOS clients Design the shared module's public API - decide what it exposes to platform-specific code and what stays internal Keep the shared module platform-clean: no Android-only imports, plain data classes and suspend functions at the platform boundary Wire up dependency injection using Metro (a newer DI tool similar to Dagger/Anvil) Package the iOS side as an XCFramework and handle Kotlin/Native interop correctly for Swift consumers Build and maintain a Jetpack Compose benchmark app on Android used to validate the shared core Work with the Android and iOS engineers to migrate their existing native code onto the shared core Required Qualifications Production experience with Kotlin Multiplatform: shared module design, expect/actual, judgment on where platform boundaries belong Experience building and shipping an SDK or library consumed by other developers - deciding what belongs in a public API and what stays closed Dependency injection experience (Dagger, Anvil, Hilt, Koin, or similar); able to pick up Metro quickly Working knowledge of Swift and iOS development, including how Kotlin/Native interop and Objective-C/Swift bridging work Jetpack Compose experience Strong Kotlin fundamentals: coroutines, suspend functions, structured concurrency Nice to Have Compose Multiplatform experience - not needed now, but a likely future direction Familiarity with Kotlin/Native specifics: memory model, concurrency constraints, interop edge cases Android or iOS production experience beyond KMP itself On-device AI / ML experience What Success Looks Like (First 6 Months) Shared KMP core in production use by both the Android and iOS clients Clean, reviewed public API for the shared module Android and iOS native code migrated onto the shared core Working Compose benchmark app used to validate changes to the core Location & Logistics Remote / flexible Reports to the CTO