Senior, DevSecOps Engineering (m/f/d)

About your tasks:

• Build and maintain secure CI/CD pipelines (Azure DevOps or GitHub Actions): secrets hygiene, signed artifacts/SBOMs, SAST/DAST/container scanning, least-privilege service connections, and supply-chain hardening.
• Automate security in infrastructure with Terraform: enforce guardrails using policy-as-code (Azure Policy, OPA/Conftest) and continuous IaC scanning (Checkov/tfsec).
• Harden Kubernetes: implement RBAC, NetworkPolicies, Pod Security Standards, secret management, image signing/scanning, and admission policies (Gatekeeper/Kyverno).
• Protect cloud identities & data: manage Entra ID roles/Managed Identities, Key Vault, Private Link/NSGs, encryption at rest/in transit, and just-in-time/least-privilege access.
• Secure ML/MLOps: lock down Databricks (Unity Catalog permissions, secret scopes), MLflow/model registry, feature stores; add model artifact signing, provenance, and runtime isolation for training/serving.
• Monitoring, logging & response: wire platform and security telemetry to Microsoft Sentinel/Defender, define alerts/runbooks, and support incident response and tabletop exercises.
• CVE & vulnerability management: maintain and publish SBOMs; continuously scan for vulnerabilities; triage CVEs (e.g., CVSS scoring + exploitability context), coordinate mitigations/patches, track exposure windows and SLAs, verify remediation, and report metrics to SecOps/GRC.
• Concepts & architecture: draft and maintain reference architectures, trust-boundary diagrams, data-classification schemes, environment isolation patterns, secure secret/key management patterns, and network segmentation for AI services.
• Compliance & assurance: contribute to risk assessments and threat modeling (incl. AI-specific risks: prompt injection, data exfiltration, model theft), support DPIAs, vendor/third-party risk reviews, penetration tests, control testing, evidence collection, and audit readiness for ISO 27001, GDPR, and EU AI Act/NIS2 where applicable.
• Governance: maintain security baselines and exceptions, own platform security KPIs, ensure retention policies, access reviews, and end-to-end audit trails (code → data → model → deployment).