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DevSecOps / Platform Engineer (Kubernetes/Terraform) — Full Remote Portugal

Roles & Responsibilities

  • 7+ years in DevOps / Platform Engineering
  • 2+ years in a dedicated DevSecOps capacity
  • Deep Kubernetes expertise (AKS, upstream K8s, or enterprise distributions) with hands-on experience in on-prem Kubernetes (RKE2, K3s, OpenShift) and GPU-accelerated workloads management
  • IaC and CI/CD expertise: Terraform, Helm, Kustomize, YAML; GitOps workflows; and CI/CD pipelines with Azure DevOps and/or GitHub Actions

Requirements:

  • Own and shape the reliability, security posture, and scalability of the Kubernetes-based platform across cloud (AKS) and on-prem environments
  • Drive GitOps-first culture with Infrastructure as Code, auditable changes, and ownership of CI/CD pipelines (Azure DevOps and/or GitHub Actions)
  • Design and operate GPU-accelerated ML workloads on Kubernetes (NVIDIA operators, GPU device plugins, Run:AI) and ensure robust, scalable deployment
  • Implement and maintain security tooling and observability: CIS hardening, zero-trust architecture, container security, secret management (Vault/Key Vault), Keycloak identity, Prometheus/Grafana dashboards, TLS and certificate lifecycle, RBAC/NetworkPolicies

Job description


ABOUT THE OPPORTUNITY

Join a technically ambitious organisation operating at the intersection of infrastructure, security, and cutting-edge AI/ML workloads. This is a senior individual contributor role where your work directly shapes the reliability, security posture, and scalability of critical platform infrastructure. You'll be embedded in a high-trust engineering culture that values ownership, technical depth, and continuous improvement — not ticket-pushing.

The environment is complex, the challenges are real, and the impact is immediate. If you thrive in platforms where GPU-accelerated workloads, zero-trust security, and cloud-native tooling converge, this role was built for you.

PROJECT & CONTEXT

You will be working on a mature but evolving internal platform that supports advanced data and ML workloads running on Kubernetes across both cloud (AKS) and on-premises environments. The platform serves cross-functional engineering teams and demands the highest standards in security hardening, observability, and operational resilience.

The stack is modern, the team is senior, and the expectations are high — in the best possible way. You'll be operating in a GitOps-first, security-first culture where Infrastructure as Code is the norm and every change is deliberate and auditable.

WHAT WE'RE LOOKING FOR (Required)

Experience

  • 7+ years in DevOps / Platform Engineering
  • 2+ years in a dedicated DevSecOps capacity

Kubernetes & Infrastructure

  • Deep expertise in Kubernetes — AKS, upstream K8s, or enterprise distributions
  • Hands-on experience with on-premises Kubernetes: RKE2, K3s, or OpenShift
  • IaC proficiency: Terraform, Helm, Kustomize, YAML, GitOps workflows
  • CI/CD pipeline ownership: Azure DevOps and/or GitHub Actions

GPU & ML Workloads

  • Experience deploying and managing GPU-accelerated workloads using NVIDIA operators, GPU device plugins, and/or Run:AI

Security (Non-Negotiable)

  • CIS-hardened Kubernetes environments
  • Zero Trust network architecture principles
  • Container security tooling: Trivy, Aqua, Prisma, or equivalent
  • SAST/DAST/SCA toolchain implementation
  • RBAC, NetworkPolicies, PodSecurityAdmission configuration
  • Encryption at rest and in transit; certificate lifecycle management
  • Secrets management: HashiCorp Vault and/or Azure Key Vault
  • Keycloak configuration and identity management

Observability

  • Prometheus and Grafana — deployment, configuration, and dashboard ownership

Networking & Linux

  • Strong Linux fundamentals and networking depth: TLS, DNS, Ingress, OAuth/OIDC, VNet, Peering, VPN/Jump Host configuration

Data & Storage

  • Experience managing MinIO, MLflow, and PostgreSQL (HA configurations and backup strategies)

Scripting & Languages

  • Strong scripting in Python and Bash (required)

NICE TO HAVE (Preferred)

  • Experience supporting ML platforms: Kubeflow, MLflow, KServe
  • Knowledge of distributed storage systems: Ceph or NetApp
  • Background in regulated industries — automotive, aerospace, medical, energy, or railway
  • Scripting experience in Go

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