Kubernetes Administrator – AI Infrastructure

Sira Consulting, an Inc 5000 company; United States; On-site; USD 140,000 - 210,000; Full time

Job summary

Sira Consulting is seeking a Senior Kubernetes Administrator / Platform Engineer to own and operate Kubernetes platforms for AI, GPU, and data-intensive workloads. The role emphasizes hands-on troubleshooting, automation, and Linux administration in a remote, US-based setting.

The ideal candidate has 7+ years in infra/platform engineering, deep Kubernetes knowledge, and experience with GPU workloads, Helm, and GitOps. Collaboration with SRE and Validation teams is key.

Qualifications

• 7+ years of infra/platform engineering with hands-on Kubernetes.
• Strong understanding of Kubernetes internals and troubleshooting.
• Experience with container runtimes, Helm, GitOps, and cluster lifecycle management.
• Experience supporting GPU workloads on Kubernetes in production or validation environments.
• Strong Linux administration and data center network knowledge.
• Ability to troubleshoot across nodes, pods, networking, storage, and control-plane layers.
• Scripting/automation: Python, Bash, or Go.

Responsibilities

• Build, administer, and troubleshoot Kubernetes platforms supporting AI and data-intensive workloads.
• Troubleshoot control plane, kubelet, CNI, CSI, ingress, service discovery, scheduling, container runtime, and resource issues.
• Support GPU-enabled Kubernetes environments, including device plugins and node health.
• Improve platform reliability through automation, standardized configurations, upgrade planning, and cluster validation.
• Troubleshoot storage, network policies, DNS, image pulls, autoscaling, pod eviction, and degraded nodes.
• Collaborate with Linux, Network, SRE, and Validation teams to resolve cross-layer infrastructure issues.
• Develop reusable runbooks, dashboards, health checks, and operational procedures for day-2 support.
• Contribute to platform hardening, tenant readiness, monitoring, and SLAs.

Skills

Kubernetes administration

Cluster troubleshooting

Automation scripting

Linux administration

GPU workloads on Kubernetes

Python Bash Go

GitOps / declarative operations

Container runtimes

Tools

Kubernetes

Helm

GitOps

Kubectl

Container runtimes

Job description

Location: Remote

Job Summary

We are seeking a Senior Kubernetes Administrator / Platform Engineer with strong hands-on experience managing Kubernetes platforms for AI, GPU, and data-intensive workloads. The ideal candidate should have strong cluster troubleshooting, automation, containerization, and Linux administration skills.

Key Responsibilities

• Build, administer, and troubleshoot Kubernetes platforms supporting AI and data-intensive workloads.
• Troubleshoot control plane, kubelet, CNI, CSI, ingress, service discovery, scheduling, container runtime, and resource issues.
• Support GPU-enabled Kubernetes environments, including device plugins, drivers, node health, and workload placement.
• Improve platform reliability through automation, standardized configurations, upgrade planning, and cluster validation.
• Troubleshoot issues involving storage, network policies, DNS, image pulls, autoscaling, pod eviction, and degraded nodes.
• Collaborate with Linux, Network, SRE, and Validation teams to resolve cross-layer infrastructure issues.
• Develop reusable runbooks, dashboards, health checks, and operational procedures for day-2 support.
• Contribute to platform hardening, tenant readiness, monitoring, and service-level objectives.

Required Skills

• 7+ years of infrastructure/platform engineering experience with deep hands-on Kubernetes administration.
• Strong understanding of Kubernetes internals and cluster troubleshooting.
• Experience with container runtimes, Helm, GitOps/declarative operations, and cluster lifecycle management.
• Experience supporting GPU workloads on Kubernetes in production, lab, or validation environments.
• Strong Linux administration skills and understanding of data center network dependencies.
• Ability to troubleshoot issues across nodes, pods, networking, storage, and control-plane layers.
• Strong scripting and automation skills using Python, Bash, or Go.

Preferred Skills

• Experience with Kubeflow, Argo, Prometheus, Grafana, Loki, or service mesh technologies.
• Familiarity with bare-metal Kubernetes and high-performance storage/networking.
• Experience working in regulated or high-change-control production environments.
• Knowledge of AI/ML infrastructure, GPU clusters, and distributed workloads.