AI Platform Engineer
Xebia · Romania
- Hybrid
- Full-time
- $120,000 / year
- Romania
Job highlights
- Shape AI platform architecture across cloud.
- Lead infrastructure automation and deployment.
- Manage Kubernetes, CI/CD, and container images.
- Enhance system reliability and production readiness.
- Collaborate with engineering teams for operations.
About the role
About Xebia
Xebia is a global tech company with a strong presence in CEE, formed by the integration of PGS Software and GetInData. We are a team of over 1,000 experts specializing in cloud, data, and software solutions. We are expanding and looking for passionate individuals to join our journey.
What We Do
We engage in impactful projects across diverse industries such as fintech, e-commerce, aviation, logistics, media, and fashion. We leverage technologies like ML, LLMs, and Generative AI to help clients build scalable platforms, data-driven solutions, and next-gen applications. Our clients include well-known companies like Spotify, Disney, ING, UPS, Tesco, and many others. We are proud partners of Databricks, dbt, Snowflake, Azure, GCP, and AWS, and were the first AWS Premier Partner in Poland.
Beyond Projects & Community
At Xebia, our community is a key differentiator. We organize events like the Data&AI Warsaw Summit and regular meetups. We foster a culture of continuous growth through Guilds, Labs, and personal development budgets, supporting both technical and soft skills development. This is more than just a job; it’s a place to grow.
Role Responsibilities
- Shaping and evolving the AI platform architecture across cloud infrastructure and application services.
- Leading platform deployment activities and infrastructure automation initiatives.
- Owning and maintaining Kubernetes manifests, CI/CD pipelines, and container build images.
- Driving system hardening, reliability, and production readiness improvements.
- Making key architectural decisions connecting platform, infrastructure, and application layers.
- Collaborating with engineering teams to support scalable and efficient platform operations.
Your Profile
- 5+ years of relevant experience.
- Practical experience using AI-powered assistants (e.g., Claude Code, GitHub Copilot, Cursor) to improve productivity, quality, or decision-making in software delivery.
- Strong expertise in Terraform (preferred) or similar IaC tools, Helm, and GitOps (Argo CD/Flux a plus).
- Experience with CI/CD (e.g., GitHub Actions).
- Deep knowledge of production Kubernetes (deployments, services, HPA, RBAC, etc.).
- Experience with multi-orchestrator environments (Kubernetes + AWS ECS, GCP Cloud Run, Azure, etc.).
- Solid understanding of data management and Python development.
- Familiarity with observability tools (e.g., OpenTelemetry, Prometheus, Grafana).
- 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
Key skills/competency
AI Platform Engineer, Cloud Infrastructure, Application Services, Platform Deployment, Infrastructure Automation, Kubernetes, CI/CD, Terraform, GitOps, System Hardening, Reliability, Production Readiness, Architectural Decisions, Python Development, Observability Tools.
Skills & topics
- AI Platform Engineer
- Cloud Engineer
- DevOps Engineer
- Kubernetes
- Terraform
- CI/CD
- Python
- AWS
- GCP
- Azure
- Data Management
- LLM
- Generative AI
How to get hired
- Research Xebia's culture: Understand their focus on cloud, data, and software, and their community-driven approach.
- Tailor your resume: Highlight your 5+ years of experience, specific AI tool usage, and expertise in Kubernetes, Terraform, and CI/CD.
- Showcase AI productivity: Emphasize practical experience using AI assistants like GitHub Copilot in software delivery.
- Prepare for technical interviews: Be ready to discuss your deep knowledge of Kubernetes, multi-orchestrator environments, and observability tools.
- Demonstrate collaboration: Highlight your experience working with engineering teams to ensure scalable platform operations.
Technical preparation
Behavioral questions
Frequently asked questions
- What are the primary responsibilities of an AI Platform Engineer at Xebia?
- As an AI Platform Engineer at Xebia, you will be responsible for shaping the AI platform architecture, leading deployment and automation initiatives, managing Kubernetes and CI/CD pipelines, enhancing system reliability, making key architectural decisions, and collaborating with engineering teams for efficient platform operations.
- What experience is required for the AI Platform Engineer role at Xebia?
- We require 5+ years of relevant experience, practical use of AI-powered assistants for software delivery, strong expertise in Terraform or other IaC tools, Helm, GitOps, CI/CD (like GitHub Actions), deep knowledge of production Kubernetes, experience with multi-orchestrator environments, solid data management and Python development understanding, and familiarity with observability tools.
- Does Xebia offer opportunities for professional growth for an AI Platform Engineer?
- Absolutely. Xebia fosters a culture of continuous growth through Guilds, Labs, and personal development budgets for both technical and soft skills. We also organize industry events and meetups, providing ample opportunities to expand your knowledge and network.
- What is the recruitment process for the AI Platform Engineer position at Xebia?
- The recruitment process typically involves a CV review, an HR call, a technical interview, and a client interview, culminating in a decision. We aim to provide a thorough and efficient process for all candidates.
- Can I work remotely as an AI Platform Engineer for Xebia?
- This role requires you to work from the European Union region and have a valid work permit. While not fully remote in a global sense, it offers the opportunity to work within the EU.
- What AI technologies and tools are prominent in Xebia's projects?
- Xebia works with ML, LLMs, and Generative AI. We are partners with Databricks, dbt, Snowflake, and major cloud providers like AWS, GCP, and Azure, utilizing modern, open-source stacks for our client projects.
- How does Xebia support the use of AI tools by its engineers?
- Xebia encourages practical experience with AI-powered assistants like Claude Code, GitHub Copilot, and Cursor to enhance productivity, quality, and decision-making in software delivery. There's also a 'nice to have' for applying GenAI more structurally within the SDLC.