Senior Android Engineer, AI Integrated Enterprise Applications

What You'll Do - Own architecture and design across feature teams for enterprise grade, high scale Android applications - Build and maintain scalable Gradle architectures and high performance Jetpack Compose UIs - Integrate LLM APIs and MCP (Model Context Protocol) frameworks directly into production apps, handling token management, context handling, agentic workflows, multi agent orchestration, and AI error recovery - Diagnose memory leaks and ANR issues, implement Firebase Crash Reporting, and drive performance across distributed services - Apply Hilt/Dagger dependency injection and MVVM/Clean Architecture to keep the codebase testable as the team scales - Ship through the full app lifecycle, from early build to Google Play Store release, inside a CI/CD driven workflow What You Bring - 5+ years coding Android, building enterprise mobile applications at global scale - 3+ years hands on with Kotlin, current on the latest language updates - Strong grasp of Android SDK, Jetpack libraries, security modules, and object oriented design patterns - Solid understanding of multi threading, memory management, and caching on mobile - Strong problem solving fundamentals, algorithms and data structures - Working knowledge of MVVM, Clean Architecture, dependency injection, and functional programming - At least 2 to 3 of the following: Kotlin Coroutines and Flow, DataStore and Room, OkHttp and Protocol Buffers, WorkManager - Postgraduate degree in Computer Science or related field, or equivalent industry experience Bonus Points - Hands on experience integrating LLM platforms such as Claude, OpenAI, or MCP tool servers - Active GitHub portfolio with multiple Android projects showing real architectural depth - Open source contributions or technical writing on Android or AI adjacent topics Who Thrives Here - Influences multiple teams through technical depth, not authority - Owns problems without needing to be micromanaged - Can present architectural tradeoffs to senior and executive stakeholders as easily as debugging an ANR at 2am