Designs and maintains large-scale, multi-module Android applications using Kotlin, Jetpack Compose, Gradle, and scalable architecture. Responsibilities include optimizing builds and app performance, diagnosing memory issues and ANRs, implementing dependency injection and automated testing, and analyzing Firebase Crashlytics data. The engineer also integrates LLM APIs, MCP frameworks, token and context management, agentic workflows, multi-agent orchestration, and AI recovery strategies into production mobile applications while collaborating across engineering, product, QA, and architecture teams.
We are looking for an experienced Android Engineer to design, develop, and maintain large-scale, multi-module Android applications for digital banking products.
The ideal candidate should have strong hands-on expertise in Android, Kotlin, Jetpack Compose, Gradle, modular application architecture, performance optimization, and automated testing, along with practical experience integrating LLM/AI capabilities into production applications.
The role requires someone who can work across complex Android architectures, optimize build and application performance, and contribute to AI-powered mobile experiences while maintaining strong engineering, scalability, reliability, and testing standards.
RequirementsKey Responsibilities
- Design, develop, and maintain large-scale, multi-module Android applications.
- Build scalable and maintainable Android architectures across multiple feature teams.
- Design and optimize complex Gradle build architectures and improve build performance.
- Develop high-performance, responsive user interfaces using Jetpack Compose.
- Implement robust Firebase Crash Reporting and analyze crash and stability issues.
- Diagnose and resolve memory issues, ANRs, performance bottlenecks, and application stability problems.
- Implement scalable dependency injection patterns using Hilt/Dagger.
- Develop highly testable and maintainable Android solutions across multiple modules and feature teams.
- Integrate LLM APIs and AI capabilities into production Android applications.
- Work with Model Context Protocol (MCP) frameworks and MCP-based integrations in production environments.
- Implement and work with token management and context handling for LLM-powered applications.
- Design and integrate agentic AI workflows and multi-agent orchestration where required.
- Implement appropriate AI error recovery and failure-handling strategies.
- Collaborate with engineering, product, QA, architecture, and other cross-functional teams.
- Contribute to code reviews, technical design discussions, engineering standards, and architectural decisions.
- Balance architectural scalability with practical mobile constraints including performance, memory, reliability, and user experience.
Android Development
- Strong hands-on experience in Android development.
- Strong proficiency in Kotlin.
- Experience developing large-scale and multi-module Android applications.
- Strong understanding of scalable Android architecture and modular design.
- Advanced experience with Gradle and complex Android build systems.
- Experience optimizing Android build performance.
- Strong hands-on experience with Jetpack Compose and modern Android UI development.
- Experience with Firebase Crash Reporting/Crashlytics and production crash analysis.
- Strong experience diagnosing memory issues, ANRs, and application performance problems.
- Strong understanding and practical experience with Hilt and/or Dagger for dependency injection.
Hands-on production experience with AI integration is required.
Candidates should have experience with:
- LLM API integration within applications.
- Working with LLM platforms such as Claude, OpenAI, or similar platforms.
- Model Context Protocol (MCP) and MCP frameworks/tool servers.
- Token management and optimization.
- Context management and handling.
- Agentic AI workflows.
- Multi-agent orchestration.
- AI error handling and recovery strategies.
- Integrating AI-powered features into production applications.
Strong experience in at least 2–3 of the following areas:
- Kotlin Coroutines & Flow
- DataStore & Room
- OkHttp & Protocol Buffers
- WorkManager
- Strong understanding of Android testing and quality engineering practices.
- Experience writing and maintaining automated tests.
- Experience with automation testing frameworks and testable Android architecture.
- Ability to build solutions with strong testability, maintainability, and reliability.
- Experience identifying and resolving production defects and stability issues.
- Experience with Android memory profiling and performance analysis.
- Strong experience with Firebase crash analysis.
- Ability to diagnose ANRs and application performance issues.
- Experience optimizing large-scale Android applications.
- Understanding of mobile performance constraints and resource management.
- Experience working with scalable, modular Android architectures.
Candidates with an active GitHub portfolio are highly preferred.
The portfolio should ideally demonstrate:
- Multiple Android projects.
- Strong Android architecture and scalability.
- Kotlin development.
- Jetpack Compose.
- AI/LLM integrations where applicable.
- Clean and maintainable engineering practices.
Additional strengths include:
- Open-source contributions.
- Technical writing.
- Public technical projects.
- Experience shipping AI-powered mobile features.
Experience with one or more of the following will be highly valued:
- Claude / Anthropic
- OpenAI APIs
- MCP tool servers
- LLM-powered applications
- Agentic AI systems
- AI-powered mobile features
- AI-assisted development workflows
We are looking for an engineer who can combine strong Android engineering fundamentals with modern AI capabilities.
The ideal candidate should be able to:
- Think architecturally while remaining hands-on.
- Work effectively within complex multi-module Android environments.
- Build scalable and high-performance mobile applications.
- Understand real-world mobile constraints.
- Troubleshoot difficult production issues.
- Work collaboratively across feature and engineering teams.
- Learn and adapt to rapidly evolving AI technologies.
- Translate AI/LLM capabilities into practical, production-ready mobile features.
- Maintain a strong focus on engineering quality, reliability, scalability, and user experience.
Bachelor's degree in Computer Science, Information Technology, Software Engineering, or a related technical discipline, or equivalent industry experience.
Preferred ExperienceExperience working on:
- Digital Banking
- Mobile Banking
- Financial Services
- Digital Products
- Large-scale consumer applications
- AI-powered mobile applications
- Enterprise-scale Android platforms
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