Who We Are
While Xebia is a global tech company, our journey in CEE started with two Polish companies – PGS Software, known for world-class cloud and software solutions, and GetInData, a pioneer in Big Data. Today, we’re a team of 1,000+ experts delivering top-notch work across cloud, data, and software. And we’re just getting started.
What We Do
We work on projects that matter – and that make a difference. From fintech and e-commerce to aviation, logistics, media, and fashion, we help our clients build scalable platforms, data and AI solutions, and cutting-edge applications to shape the future of tech. Our clients include McLaren, Aviva, Deloitte, Spotify, Disney, ING, UPS, Tesco, Truecaller, AllSaints, Volotea, Schmitz Cargobull, Allegro, InPost, and many, many more.
We value smart tech, real ownership, and continuous growth. We use modern, open-source stacks, and we’re proud to be trusted partners of Databricks, dbt, Snowflake, Azure, GCP, and AWS. Fun fact: we were the first AWS Premier Partner in Poland!
Beyond Projects
What makes Xebia special? Our community. We support tech communities, organize meetups (Software Talks, Data Tech Talks), and have a culture that actively support your growth via Guilds, Labs, and personal development budgets — for both tech and soft skills. It’s not just a job. It’s a place to grow.
What sets us apart?
Our mindset. Our vibe. Our people. And while that’s hard to capture in text – come visit us and see for yourself.
You will be:
- analysing incident trends, toil assessments, and recurring patterns to identify automation candidates,
- prioritising the automation backlog using ROI-based scoring models, considering effort saved, frequency, and risk level,
- building automation workflows using Ansible, Python, and cloud-native tools such as AWS Lambda, Azure Functions, Google Cloud Functions,
- developing self-service runbook automations integrated with ServiceNow and CI/CD pipelines,
- implementing governance controls, including pre-approved low-risk automations, auto-notifications for medium-risk changes, and Change Board approval flows for high-risk automations,
- measuring and reporting automation outcomes, including tickets avoided, effort saved, and weekly automation releases,
- collaborating with SRE and Platform teams to ensure automations meet reliability and security standards,
- maintaining automation code within Git repositories with full IP portability from Day 1,
- delivering against automation targets,
- supporting the Automation Factory’s 5-step pipeline: Input, Prioritise, Build, Govern, and Measure.
Your profile:
- 3 - 6 years of experience in automation engineering, DevOps, or infrastructure automation,
- practical experience using AI-powered assistants (e.g. Claude Code, GitHub Copilot, Cursor) to improve productivity, quality, or decision-making in software delivery,
- strong programming skills in Python and/or Ansible,
- experience building CI/CD pipelines using tools such as Jenkins, GitLab CI, or GitHub Actions,
- familiarity with cloud automation technologies including AWS Lambda, Azure Functions, and Terraform,
- experience integrating ITSM platforms, particularly ServiceNow APIs and workflow automation,
- understanding of change management processes and governance frameworks,
- proficiency with version control systems such as Git and code review best practices,
- good English communication skill (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,
- experience with Kubernetes operators or custom controllers,
- familiarity with ChatOps and self-service automation patterns,
- knowledge of SRE practices and toil elimination methodologies,
- experience working in managed services or large-scale operations environments,
- exposure to AIOps and ML-driven automation prioritisation.
Recruitment Process:
CV review – HR call – Technical Interview – Client Interview – Decision
