Senior DevOps Engineer (m/f/d)

About the role

We are looking for a Senior DevOps Engineer to lead the design, deployment and operation of enterprise‑grade Kubernetes platforms on Nutanix infrastructure. The role focuses on supporting AI/ML workloads, ensuring scalability, resilience and security across hybrid environments.

Key responsibilities

• Deploy, administer and optimise enterprise Kubernetes clusters on Nutanix, guaranteeing high availability and performance.
• Design infrastructure for AI/ML workloads, including GPU‑enabled nodes, model deployment frameworks and large‑scale data pipelines.
• Automate provisioning and configuration using Terraform, Ansible, Helm and GitOps practices.
• Build and maintain CI/CD pipelines for containerised applications and machine‑learning workflows.
• Implement monitoring, logging, tracing and alerting with Prometheus, Grafana, ELK and OpenTelemetry.
• Enforce security controls such as RBAC, image governance, secrets management, network segmentation and workload protection.
• Continuously optimise cluster performance, storage utilisation, networking efficiency and compute resource allocation.
• Collaborate with AI engineers, platform architects and development teams to onboard applications and improve operational practices.
• Define and validate backup, recovery and disaster‑recovery procedures for Kubernetes platforms and associated data services.

Required profile

• Minimum 5 years of experience in DevOps, Platform Engineering, Cloud Operations or SRE.
• At least 3 years of hands‑on production Kubernetes administration.
• Strong experience with Nutanix technologies (AHV, Prism, Karbon, Files, Objects).
• Proven track record supporting AI/ML platforms such as Kubeflow, MLflow, KServe or Ray.
• Bachelor’s degree in Computer Science, IT, Engineering or equivalent practical experience.

Required skills

• Kubernetes (cluster management, networking, storage, security)
• Nutanix (AHV, Prism, Karbon, Files, Objects)
• Infrastructure‑as‑Code: Terraform, Ansible, Helm, GitOps
• Scripting/automation: Python, Bash, Go
• GPU‑enabled clusters and NVIDIA accelerator technologies
• CI/CD tools: GitLab CI, GitHub Actions, Jenkins
• Observability: Prometheus, Grafana, ELK, OpenTelemetry
• Security controls: RBAC, container image governance, secrets management, network segmentation
• Backup, recovery and disaster‑recovery design for Kubernetes platforms