Platform Engineer*

Our Team Build platforms, solve difficult problems and help turn AI into practical tools. At BAWAG Group, our Platform Engineering team builds and operates shared cloud infrastructure, delivery tools and services that help development teams work independently. We also help teams deploy and run AI agents, while developing our own agents and automations to assist colleagues and simplify everyday work.

Our scope extends beyond the platform. We’re the team colleagues turn to when a technical challenge is unfamiliar, complex or crosses team boundaries. We get hands-on, investigate and work together to find a way forward. Our cloud environment spans Azure and AWS. Our stack includes Kubernetes on AKS and EKS, ECS, Argo CD, Istio, GitHub, Jenkins, Azure DevOps and HCP Vault, alongside a broad range of projects from the CNCF ecosystem.

You’ll bring practical experience in parts of this stack and the curiosity and confidence to get hands-on with the rest. Why join us Your work will shape how development teams across BAWAG Group build, deploy and operate software. You’ll influence technical decisions, take improvements from idea to production and see colleagues benefit from what you build.

The role offers breadth across Azure, AWS and cloud-native engineering, with the opportunity to help shape our growing AI capabilities. You’ll help teams put agents into production and develop tools that make everyday work easier. We’re developing our platform as a product. You’ll work directly with the people using it, understand where they get stuck and help turn recurring problems into shared capabilities.

You’ll bring your experience to difficult challenges, learn from colleagues across disciplines and help others build their expertise.

Your Responsibilities

Build, operate and improve cloud infrastructure and Kubernetes platforms, including secure configuration, upgrades, workload onboarding and migrations. Connect infrastructure as code, CI/CD and Git. Ops into reliable workflows for provisioning, deployment and recovery. Work with developers to turn recurring needs into self-service capabilities, reusable templates and clear documentation.

Help teams deploy and operate AI agents, and build agents and automations that support engineering and operational work. Investigate difficult issues across infrastructure, applications, networking and delivery systems, including challenges beyond the core platform. Turn what you learn into lasting improvements. Lead technical improvements from problem definition through design and production.

Guide decisions with application, security and operations colleagues, making trade-offs, responsibilities and recovery options clear, and share your expertise through reviews and practical guidance.

Your Profile

Experience building and operating public-cloud infrastructure and Kubernetes in production, with strong expertise in either Azure or AWS and a willingness to work across both. Practical skills in infrastructure as code, Git-based delivery and scripting or programming. A hands-on approach: you move comfortably from design discussions to reading code, changing configuration, investigating logs and testing solutions.

Curiosity and persistence when facing unfamiliar systems. You test assumptions, ask useful questions and involve others when their expertise helps. The ability to understand colleagues’ needs, explain technical trade-offs and agree workable solutions across teams. Ownership and openness: you follow through, make progress visible, raise risks early, invite review and share what you learn.

Useful additional experience Experience with AI agents, model integrations or workflow automation would be valuable, as would selected experience in observability, identity and secrets management, software supply-chain security, or cloud migrations. Familiarity with regulated environments is welcome.