Job Description - Senior Android Engineer, AI Integrated Enterprise Applications
Description
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
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