AI Applied Software Engineer

Backbase

Madrid, Spain

9 days ago

Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Experience required

5 years minimum

Working hours

Regular working hours

Job source

www.adzuna.es

Tech stack

Multitier Architecture Artificial Intelligence Android Software Development Build Automation Automation of Tests Unit Testing Mobile Application Development Continuous Integration Persistent Data Structure DevOps Programming Tools Gradle

+11 more

Model View ViewModel Mobile Security Software Engineering Circleci Large Language Models Prompt Engineering Kotlin Jetpack Compose Virtual Agents Asynchronous Programming Jenkins

Job description

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.

Requirements

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.