DevOps Engineer

Senior DevOps & Platform Engineer (Internal Developer Platform, DevSecOps, AIOps) Location: Remote within EU We are looking for a Senior / Lead Platform & DevOps Engineer with 8+ years of experience to design, build and scale an Internal Developer Platform, enterprise GitOps delivery and automated remediation across multi-cluster Kubernetes environments. The role sits in Integration Testing & Release DevOps and requires strong hands-on depth from day one. Responsibilities

• Design and standardize a self-service Internal Developer Platform (e.g. Backstage or Port) with golden deployment paths and secure, ephemeral environments
• Architect multi-cluster, multi-region GitOps delivery with ArgoCD or Flux, including automated canary analysis, traffic shadowing and automated rollbacks
• Build closed-loop remediation and AIOps pipelines using OpenTelemetry, anomaly correlation and workflow/orchestration engines (Temporal, Kubernetes Operators in Go)
• Implement policy as code and software supply chain security with Kyverno or OPA, SAST/SCA gates, cosign and SBOMs
• Define SLO/SLI governance, error budgets and automated chaos testing for distributed services
• Establish standards for IaC, CI/CD and telemetry, and drive them through cross-team RFCs and architecture reviews
• Support inference and training infrastructure for AI workloads, including GPU autoscaling (KEDA)

Required experience

• 6+ years of enterprise-scale Kubernetes in production: multi-cluster networking, service meshes (Istio/Linkerd), ingress controllers, CRD design
• Strong Go (custom operators, platform controllers) and Python (automation, data and AI pipelines)
• Modular Terraform, OpenTofu or Pulumi, including state management, drift detection and policy testing
• GitOps and delivery tooling: ArgoCD, Flux, GitHub Actions
• Observability: OpenTelemetry collector topologies, tail-based sampling, Prometheus, Grafana (Mimir/Tempo), ClickHouse or Datadog
• Policy as code and supply chain security: Kyverno, OPA, SAST/SCA, cosign, SBOMs
• Deterministic, idempotent workflows with Temporal or event-driven architectures on Kafka
• Track record of authoring cross-team RFCs and defining operational SLOs/SLIs
• Cloud: AWS and/or GCP
• Incident tooling: PagerDuty, Incident.io, Slack API

Nice to have

• Integration of ITSM/CMDB platforms (iTop or similar) into automated incident workflows
• Experience integrating LLM tool-calling, agentic triage or RAG-based runbook retrieval into incident response
• AI inference infrastructure (Ray, vLLM, Triton, Kubeflow)
• Contributions to CNCF/open-source projects