AI Platform Security Engineer
Munich, Germany — Hybrid
Deep Tech | AI Infrastructure | Platform Security | Kubernetes Security
Our client, a growing Deep Tech / AI company based in Munich, is looking for an AI Platform Security Engineer to secure the infrastructure used to train, deploy, and serve production AI models.
You'll work at the intersection of AI Infrastructure, Platform Engineering, and Cloud Security, building security directly into Kubernetes, GPU environments, workload identity, containers, and infrastructure automation.
What You'll Work On
• Secure Kubernetes platforms supporting AI training and inference workloads
• Design and enforce workload identity and least-privilege access controls
• Implement Kubernetes security policies using OPA / Kyverno
• Secure container images, registries, and runtime environments
• Build automated security tooling and controls in Python
• Provision secure infrastructure using Terraform
• Harden GPU-enabled compute environments and AI workloads
• Automate security checks across infrastructure and deployment pipelines
• Manage IAM policies, service identities, secrets, and machine-to-machine access
• Identify and remediate vulnerabilities and misconfigurations across the AI platform
• Partner with ML, Platform, and Infrastructure Engineers to make secure deployment the default
Core Skills
• 4+ years in Platform Security, Cloud Security, DevSecOps, Kubernetes Security, or similar roles
• Kubernetes
• IAM / workload identity
• Python
• Terraform
• OPA and/or Kyverno
• Container security
• Experience securing cloud-native production infrastructure
Nice to Have
NVIDIA / GPU infrastructure
Kubernetes GPU Operator
AWS / GCP
Vault / secrets management
Falco / runtime security
Trivy or similar container scanning tools
Argo CD / GitOps
SBOM and software supply-chain security
SPIFFE / SPIRE
Admission controllers
ML platforms or production AI infrastructur