DevOps Architect / Lead Platform Engineer

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.

QUALIFICATIONS & COMPETENCIES

• 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

AREA OF RESPONSIBILITY

• 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)

At RDT we develop global engineering and information technology solutions that allow our clients to gain a competitive advantage in the development of projects with advanced technological components. We offer our clients agility, flexibility, excellence and a cutting-edge approach from a sustainable and lasting perspective, positioning ourselves as a trusted strategic partner. We work in sectors such as Aeronautics, Aerospace, Automotive, Energy, Industrial, Petrochemical, Capital Goods, Consumer Goods and many more.