Senior AI Applied Software Engineer (Android)

Backbase — Netherlands · Posted ~23 hours ago

Senior Full-time

Skills

Android development Kotlin Jetpack Compose Coroutines MVVM Mobile architecture CI/CD Software testing Android Gradle LLM tools

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Summary

A senior Android engineer is needed to architect secure mobile SDKs, integrate AI-assisted development workflows, improve engineering standards, and mentor developers while owning complete mobile solutions.

Highlights

Senior technical role focused on AI-enhanced mobile engineering, architecture leadership, mentoring, and building high-quality mobile platforms.

Description

The job in short As a Senior Applied AI Software Engineer (Android), you will serve as a technical anchor for our mobile identity and banking suites—shaping SDK architectures that impact over 100 million users worldwide. You will lead the shift toward AI-native mobile development, combining deep Android architecture expertise with agentic AI tooling to set new productivity and quality benchmarks. Meet the job AI-Native Mobile Leadership: Champion the integration of LLM workflows, prompt engineering, and agentic AI tooling into the mobile engineering life cycle. Core Mobile & SDK Architecture: Architect scalable, secure Android SDKs, libraries, and modular mobile components using Kotlin, Jetpack Compose, and Coroutines. Full-Lifecycle Ownership: Own end-to-end mobile capabilities—from local data persistence and security layers to backend API integrations and CI/CD pipelines. Quality & Testing Champion: Maintain an uncompromising focus on quality, enforcing automated test coverage targets (80%+ unit testing) and performance profiling. Mentorship & Standard Setting: Mentor mobile developers, advocate best practices in mobile architecture, and establish shared engineering standards across the team. How about you Experience: 5 to 7+ years of professional software engineering experience with a heavy focus on native Android development. Tech Mastery: Advanced mastery of Kotlin, Jetpack Compose, Coroutines, Clean Architecture/MVVM, and building modular mobile SDKs used by external teams. Proven AI Production Experience: Active, hands-on production use of AI-driven developer tooling, agentic workflows, or mobile build automation. DevOps & Tooling: Deep understanding of mobile CI/CD automation tools (Bitrise, Jenkins, Gradle scripting) and non-functional requirements (mobile security, performance). Leadership Skills: Proven capacity to mentor peers, evaluate complex trade-offs, and guide autonomous squads toward clear technical goals.