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:
- supporting and driving cloud migration initiatives across business-critical systems,
- designing, building, and maintaining CI/CD pipelines in Azure DevOps,
- managing and optimizing Azure-based infrastructure and application environments,
- automating infrastructure provisioning and configuration using Infrastructure as Code practices,
- collaborating with development and architecture teams to ensure reliable and scalable deployments,
- improving platform security, performance, and operational efficiency,
- supporting application services and cloud-native solutions throughout the software delivery lifecycle.
Your profile:
Nice to have:
- experience with AWS migration programmes (e.g. MAP or similar initiatives),
- familiarity with React, Node.js, or EventStoreDB in hybrid architectures,
- exposure to FinOps practices and cloud cost optimisation initiatives,
- experience integrating AI tools into engineering workflows (CI/CD, IaC, automation),
- experience with enterprise-scale policy governance (Azure Policy, guardrails),
- 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 – Technical interview – Client Interview – Decision
