Employment Type-
- Design, develop, enhance, and maintain native Android applications using Kotlin and Java.
- Use AI-assisted development tools such as GitHub Copilot, Claude, or equivalent tools for coding, refactoring, debugging, documentation, and test generation.
- Review and validate AI-generated code for correctness, security, performance, maintainability, and compliance before integration.
- Build reusable, scalable components using MVVM, Clean Architecture principles, and separation of concerns.
- Integrate REST APIs and third-party services using Retrofit, OkHttp, JSON, and related libraries.
- Investigate and resolve defects, crashes, memory issues, and performance bottlenecks.
- Write unit tests and support automated and regression testing to maintain application quality.
- Participate in code reviews, technical discussions, estimation, sprint planning, and Agile delivery.
- Collaborate with backend developers, QA engineers, architects, product stakeholders, and project managers.
- Contribute to application modernisation, refactoring, dependency upgrades, technical-debt reduction, and performance improvements.
- Follow secure coding practices and client-specific requirements for source-code confidentiality and approved AI tool usage.
- Identify opportunities to improve engineering workflows through responsible AI adoption.
3. Mandatory Technical Skills
- 4-7 years of professional experience in native Android application development.
- Strong Kotlin skills and good working knowledge of Java.
- Strong understanding of Android SDK, application lifecycle, background processing, threading, and memory management.
- Hands-on experience with Android Jetpack components, including ViewModel, LiveData or StateFlow, Navigation, Room, and Jetpack Compose.
- Strong understanding of MVVM, Clean Architecture principles, and separation of concerns.
- Hands-on experience with Kotlin Coroutines and asynchronous programming.
- Experience integrating RESTful APIs using Retrofit, OkHttp, JSON, and third-party libraries.
- Practical experience with dependency-injection frameworks such as Hilt or Dagger.
- Experience with Firebase, Crashlytics, Sentry, or similar application monitoring and crash-reporting tools.
- Proficiency in Git, branching strategies, and collaborative source-control workflows.
- Hands-on experience with Gradle, Android Gradle Plugin, build configuration, dependency management, and Android SDK upgrades.
- Experience with CI/CD pipelines and automated build and deployment processes.
- Strong debugging, profiling, crash analysis, memory management, and performance-optimisation skills.
- Experience writing unit tests and supporting automated and regression testing.
- Understanding of secure authentication and API security practices, including JWT and OAuth 2.0.
- Practical experience using AI-assisted development tools such as GitHub Copilot, Claude, or equivalent tools.
4. AI-Assisted Development Requirements
- Demonstrated experience incorporating AI-assisted development into the software development lifecycle.
- Ability to write effective prompts to generate, analyse, debug, and improve Android code.
- Experience using AI tools for code generation, refactoring, test-case creation, technical documentation, and understanding existing codebases.
- Experience using AI assistance to understand legacy applications, modernise code, and reduce technical debt without compromising existing functionality.
- Ability to review AI-generated code for correctness, edge cases, security vulnerabilities, performance, and maintainability.
- Understanding of AI-generated code limitations, including incorrect outputs, unsupported assumptions, and dependency risks.
- Compliance with client-specific policies for AI tool usage, source-code sharing, confidentiality, and data protection.
- Full ownership of the quality, correctness, and maintainability of AI-assisted code delivered to production.
5. Additional Expectations
- Independently analyse requirements and translate them into technical solutions.
- Participate in code reviews, technical discussions, sprint planning, estimation, and Agile ceremonies.
- Collaborate effectively across Android, backend, QA, and project-management teams.
- Deliver reliable, maintainable, and scalable Android features within agreed timelines.
- Continuously improve development productivity and engineering quality through responsible AI adoption.
Android Developer JD | AI-Assisted Development
