Description
Xebia is a global AI-first, digital transformation, and engineering partner. With over 25 years of experience and a team of 5,000 professionals across 16 countries, we help organizations design and build scalable products, platforms, and data-driven solutions.
We specialize in Artificial Intelligence, Data and Cloud, Intelligent Automation, and Digital Products, combining deep technical expertise with a strong focus on engineering excellence and a people-first culture.
In the CEE region, we’re a team of nearly 1,000 experts delivering modern applications, data platforms, and AI solutions for clients such as McLaren, Aviva, Deloitte, Spotify, Disney, ING, UPS, Tesco, Truecaller, AllSaints, Volotea, Schmitz Cargobull, Allegro, InPost, and many, many more. We work with leading technologies including AWS, Azure, GCP, Databricks, and Snowflake, and combine strong engineering culture with a consulting mindset and a continuous focus on growth and knowledge sharing.
You will be:
- designing, developing, and maintaining high-quality Android applications using Java and Kotlin,
- collaborating with cross-functional teams to deliver scalable, user-focused features end-to-end,
- contributing to app architecture decisions and continuously improve performance and code quality,
- integrating mobile applications with backend services and handle asynchronous data flows,
- troubleshooting, debugging, and resolving complex issues in production environments while supporting ongoing improvements.
Your profile:
- 6+ years of professional experience in Android development,
- strong knowledge of the Android SDK,
- strong knowledge of Kotlin,
- good knowledge of Java,
- experience working with RESTful APIs and gRPC,
- excellent debugging and problem-solving skills,
- practical experience using AI-powered assistants (e.g. Claude Code, GitHub Copilot, Cursor) to improve productivity, quality, or decision-making in software delivery,
- work from the European Union region and a work permit are required.
Nice to have:
- experience with automation testing,
- experience with in-house device farm,
- familiarity with automation tools like GitHub Actions and Fastlane,
- experience with mentoring and onboarding junior team members,
- experience applying GenAI in a more structured way within the SDLC, including defined workflows, prompt patterns, or tool integrations embedded into daily work,
- interest in and familiarity with emerging AI-driven practices (e.g. agent-based workflows, automation patterns, AI-augmented development), with a willingness to explore and experiment beyond standard approaches.
Recruitment Process:
CV review – HR call – Interview – Task - Client Interview – Decision
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