Sobre este puesto de Senior Android Engineer, AI Integrated Enterprise Applications en GSSTech Group
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