Senior DevOps Engineer Nutanix Kubernetes & AI Platform

Vision Unlimited

Key Responsibilities

• End-to-End Kubernetes Platform Ownership: Design, deploy, manage, and maintain production-grade Kubernetes clusters on Nutanix Karbon (or native K8s on Nutanix AHV), ensuring high availability, performance, and security.
• AI/ML Infrastructure Architecture: Architect and implement scalable, cost-efficient infrastructure tailored for AI workloadsincluding GPU orchestration, distributed training, model serving, and data-intensive pipelines.
• Infrastructure as Code (IaC): Automate provisioning and configuration of Nutanix K8s environments using Terraform, Ansible, Helm, and GitOps workflows (e.g., ArgoCD/Flux).
• CI/CD for AI Services: Build and maintain secure, efficient CI/CD pipelines for deploying AI microservices, model endpoints, and data processing jobs into K8s environments.
• Observability & SRE Practices: Implement comprehensive monitoring, logging, and alerting (using Prometheus, Grafana, ELK, OpenTelemetry, etc.) with SLO/SLI tracking for AI platform reliability.
• Security & Compliance: Enforce zero-trust networking, RBAC, pod security policies, image scanning, and secrets management (e.g., HashiCorp Vault) aligned with enterprise security standards.
• Performance Optimization: Tune K8s scheduling, storage (Nutanix Files/Objects), networking (CNI), and resource allocation (CPU/GPU/memory) for AI/ML workloads.
• Collaboration & Enablement: Partner with AI/ML engineers to onboard models and services onto the platform; document best practices and provide self-service tooling.
• Disaster Recovery & Backup: Implement and test backup/recovery strategies for K8s workloads and persistent data using Nutanix-native or third-party tools (e.g., Velero).

Required Qualifications

• 5+ years of DevOps/SRE experience with 3+ years focused on Kubernetes in production environments.
• Deep hands-on experience with Nutanix (AHV, Prism, Karbon, Files, Objects) and managing K8s on-prem or hybrid.
• Proven track record designing and operating AI/ML infrastructure (e.g., Kubeflow, MLflow, Seldon, KServe, Ray).
• Expertise in Infrastructure as Code: Terraform, Helm, Ansible, GitOps.
• Strong scripting/automation skills (Python, Bash, Go).
• Experience with GPU orchestration (NVIDIA device plugins, MIG, CUDA) in K8s.
• Solid understanding of networking, storage, and security in K8s (CNI, CSI, RBAC, OPA/Gatekeeper).
• Familiarity with CI/CD tools (GitLab CI, Jenkins, GitHub Actions) and artifact management (Harbor, JFrog).
• Experience with observability stacks (Prometheus, Grafana, Loki, Tempo, OpenTelemetry).
• Bachelors degree in Computer Science, Engineering, or equivalent practical experience.

Preferred Qualifications

• Nutanix certifications (e.g., NCP-MCI, NCP-DS).
• CNCF certifications (CKA, CKAD, CKS).
• Experience with multi-cluster management (Rancher, Anthos, OpenShift).
• Knowledge of MLOps practices and tools (MLflow, TFX, Kubeflow Pipelines).
• Experience in regulated industries (finance, healthcare) with compliance needs (SOC2, HIPAA, GDPR).