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 Millennium, ING, Play, Edenred, Arabian Drilling, FedEx, Leroy Merlin, Truecaller, Volotea, Schmitz Cargobull, and many, many more.
You will be:
- designing and implementing automations for recurring incidents, service requests, and operational processes,
- transforming manual operational tasks into scalable and governed automated workflows,
- collaborating with Platform Operations, SRE, and Service Management teams to identify automation opportunities,
- developing and maintaining Infrastructure-as-Code solutions and deployment automation,
- improving monitoring, alerting, and operational visibility to enhance service reliability,
- contributing to self-healing, auto-remediation, and continuous improvement initiatives,
- applying software engineering best practices, including testing, version control, and code reviews,
- creating reusable automation frameworks and mentoring engineers through knowledge sharing,
Your profile:
- at least 5 years of experience in Automation Engineering, DevOps, Platform Engineering, SRE, Cloud Engineering, or a similar role,
- practical experience using AI-powered assistants (e.g. Claude Code, GitHub Copilot, Cursor) to improve productivity, quality, or decision-making in software delivery,
- strong experience with Python, Infrastructure as Code, cloud platforms, CI/CD, Kubernetes, and observability,
- hands-on experience with Infrastructure as Code tools such as Terraform, Ansible, or equivalent,
- experience working with AWS, Azure, or Google Cloud Platform,
- understand CI/CD pipelines, deployment automation, and modern platform engineering practices,
- experience with Kubernetes and containerized environments,
- understand monitoring, observability, and incident management principles,
- apply software engineering best practices, including testing, version control, and peer reviews,
- demonstrate strong problem-solving and analytical skills,
- communicate effectively and collaborate well with cross-functional teams,
- a proactive mindset and a passion for improving operational efficiency through automation,
- good English communication skills (at least B2 level).
Work from the European Union region and a work permit are required.
Nice to have:
- 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
