GCP Platform Engineer

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. 

As a Cloud Platform Engineer, you will join our Managed Service Provider (MSP) practice to build, maintain, and support secure, automated, and scalable Google Cloud environments for clients. You will focus on implementing Infrastructure as Code (IaC), maintaining robust CI/CD pipelines, Handling support questions, Incident Response, and driving platform observability and health.

• Google Cloud Platform (GCP): Medior-level experience with core GCP services (Compute Engine, GKE, Cloud Storage, IAM, VPC, Cloud Functions).
• Infrastructure as Code (IaC): Solid understanding of Terraform fundamentals (resources, variables, modules, state management, basic CLI).
• CI/CD & Automation: Experience working with CI/CD tools and scripting skills (Bash, Python, or Go).
• Containers & Cloud-Native Basics: Practical experience with Docker and Kubernetes/GKE concepts.
• Observability: Familiarity with Cloud Monitoring, Cloud Logging, Prometheus, or standard APM tools.
• Ways of working: comfortable on a weekly L1↔L2 rotation and a standby/pager rotation, strong troubleshooting, communication and a team-first attitude.
Professional Experience & Mindset
• Enterprise Context: 2+ years of experience working in IT, DevOps, or Cloud Engineering roles (preferably within an MSP, consulting, or multi-team enterprise environment).
• AI-Powered Productivity: Practical experience using AI developer assistants (e.g., Claude Code, GitHub Copilot, Cursor, Gemini Code Assist) to accelerate code writing, debugging, and learning.
• Troubleshooting & Curiosity: Strong problem-solving skills with a logical approach to diagnosing technical issues.
• Collaboration & Growth: Excellent communication skills, a team-first attitude, and an eagerness to learn advanced cloud architecture patterns from senior team members.

• 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.

• 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.

CV review – HR call – Interview – Client Interview – Decision