Platform & MLOps Engineer – AI and Simulation Platforms

To support the Operational Analysis and Studies department, Airbus Defence and Space is looking for a Platform & MLOps Engineer (d/m/w) – AI and Simulation Platforms. In the "Operational Analysis and Studies" department, we develop state-of-the-art military simulation environments, AI methods (including Deep Reinforcement Learning) as well as agentic data-fusion and multi-agent solutions for ISR for the Bundeswehr, NATO and EU. To train and operate our AI models efficiently, we are building highly available, scalable cloud and MLOps infrastructures. In this role, you form the central interface between infrastructure and AI development. This position is also possible with reduced weekly working hours and an adjusted scope of tasks. Your location At the Airbus site in Immenstaad am Bodensee, you work where the future of Connected Intelligence, Space and Air Power is created. In an environment that offers perspective, you shape technological innovations across domains. Our site thrives on dialogue: On campus you meet a unique network of experts in satellite technology, military aviation, cyber security, artificial intelligence as well as Combat Cloud and Ground Support of tomorrow. Our collaboration is also characterized by dynamism – in agile teams we tackle the most complex questions, from AI-supported earth observation to secure cloud architecture. Those seeking technological excellence and interdisciplinary collaboration will find the ideal environment here. Located between Stuttgart and Munich, Ulm is a city that offers a wide range of leisure and cultural activities. Here you can enjoy the quality of life under the highest church tower in the world and be part of a city that both preserves its historical sights and actively shapes the future along the Danube.

• Platform & Cluster Operations: Setup, scaling and stable operation of Kubernetes clusters (e.g. MicroK8s, Vanilla K8s) in development context as well as in client-side air-gapped environments.
• Infrastructure Automation: Consistent use of Infrastructure as Code (Terraform, Ansible, Helm) and setup of automated CI/CD and GitOps pipelines (e.g. with GitLab).
• MLOps Integration: Seamless integration of machine learning pipelines and AI training runs into the cloud infrastructure to support data scientists.
• Observability & DevSecOps: Setup of central monitoring and logging (Prometheus, Grafana, Loki) as well as direct integration of security and IAM standards (e.g. Keycloak, Vault) into the pipelines.
• Agile Collaboration: Close coordination and collaboration in an agile, interdisciplinary team of software developers, data scientists and external partners.

• Education & Experience: Completed degree (Bachelor/Master) in Computer Science, Software Engineering, Business Informatics or a comparable qualification plus 2 to 5 years of practical experience in Platform Engineering, Cloud Architecture or DevOps.
• Container & Kubernetes: Solid knowledge in Kubernetes and container environment (Docker, Helm, K8s architecture).
• Automation & CI/CD: Routine handling of Linux systems, shell scripting, CI/CD pipelines (e.g. GitLab CI) and IaC tools (Terraform, Ansible).
• Programming & Security: Good knowledge of Python and preferably first experience with MLOps frameworks, Secret Management (Vault) and Auth services (Keycloak, OIDC).
• Languages & Soft Skills: Fluent German and English skills, structured problem-solving competence and enjoyment of knowledge sharing in the team.