DevOps Architect

RDT

Brande

Remote

DKK 673,000 - 972,000

Full time

11 days ago

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Benefits offered by this job

Remote within EU
Flexible working hours
Career development opportunities

Job summary

RDT is seeking a Senior Platform Engineer to design and scale an Internal Developer Platform, focusing on DevSecOps, GitOps delivery, and AI-enabled operations across multi-cluster Kubernetes environments. You will lead architecture, automation, and policy-as-code practices from day one.

The role covers SLO/SLI governance, automated remediation, and cross-team RFCs, while supporting AI inference workloads and GPU autoscaling. Remote within EU.

Qualifications

  • 6+ years of enterprise-scale Kubernetes in production.
  • Proficiency in Go and Python for automation.
  • Experience with GitOps delivery and multi-cluster setups.
  • Experience with policy as code and software supply chain security.
  • Experience with IaC, CI/CD and telemetry standards.
  • Experience with AI infra is a plus.

Responsibilities

  • Design and standardize a self-service Internal Developer Platform with ephemeral environments.
  • Architect multi-cluster, multi-region GitOps delivery with ArgoCD or Flux.
  • Build closed-loop remediation and AIOps pipelines using OpenTelemetry, anomaly correlation and workflow/orchestration engines.
  • Implement policy as code and software supply chain security with Kyverno or OPA.
  • 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).

Skills

Kubernetes
Go
Python
GitOps
OpenTelemetry
Terraform

Tools

ArgoCD
Flux
Pulumi
OpenTofu
Kubernetes Operators

Job description

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
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