We are seeking for experienced Android Engineer to build and maintain large-scale, multi-module Android applications with expertise in complex build systems, up-to-date Android development, and AI integration.
The role involves designing scalable Gradle architectures, optimizing application performance, developing high-performance Jetpack Compose interfaces, and integrating AI capabilities into production mobile applications.
Key Responsibilities:
Android Application Engineering
- Design scalable Gradle architectures for large-scale, multi-module Android applications.
- Optimize build performance and modular application structures.
- Develop high-performance Jetpack Compose user interfaces.
- Apply scalable and maintainable architectural patterns across feature teams.
Performance & Reliability
- Implement robust Firebase Crash Reporting.
- Diagnose memory issues and ANRs.
- Perform memory profiling, crash analysis, and application performance optimization.
- Identify and resolve performance issues across large-scale modular applications.
AI & Modern Application Development
- Integrate LLM APIs and work with MCP (Model Context Protocol) frameworks in production environments.
- Apply AI error-recovery strategies across agentic workflows and multi-agent orchestration.
- Work with token management, context handling, agentic workflows, and multi-agent orchestration.
Required Skills & Experience:
- 5+ years of experience building and maintaining large-scale, multi-module Android applications.
- Strong understanding of token management, context handling, agentic workflows, and multi-agent orchestration.
- Hands-on experience integrating LLM APIs and MCP frameworks in production environments.
- Strong expertise in 2-3 of the following:
- Kotlin Coroutines & Flow
- Data Store and Room
- OkHttp and Protocol Buffers
- Work Manager
- Experience with memory profiling, Firebase crash analysis, and performance optimization.
Preferred Skills:
- Active GitHub portfolio showcasing multiple Android projects with strong architecture and scalability.
- Open-source contributions and technical writing experience.
- Experience shipping AI-powered features.
- Experience with LLM platforms such as Claude, OpenAI, or MCP tool servers.
- Ability to balance architectural thinking with practical delivery across complex modular systems and real-world mobile constraints.