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Senior AI Applied Software Engineer at workatbackbase – Madrid | Jobyssey

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Senior AI Applied Software Engineer

Senior AI Applied Software Engineer

workatbackbase · Madrid · Yesterday

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Seniority: Senior
Category: Software engineering
Experience: 7+ years

agentic-ai ai android api automation ci-cd devops gradle jenkins jetpack kotlin llm mvvm

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prompt-engineering

Senior Android engineer leading AI-native mobile development for banking SDKs used by 100M+ users, integrating LLM workflows and agentic AI tooling with Kotlin, Jetpack Compose, and Clean Architecture.

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.