Senior Kubernetes Administrator – AI Infrastructure

HCLTech; United States; On-site; USD 78,000 - 148,000; Full time

Job summary

HCLTech is seeking a Senior Kubernetes Administrator – AI Infrastructure to lead platform engineering for AI workloads in a remote setting. You will build, troubleshoot, and scale Kubernetes platforms supporting model development, training, and inference services.

Ideal candidates have 7+ years in infrastructure, deep Kubernetes expertise, experience with GPUs, Helm, GitOps, and strong Linux networking. Remote work with competitive compensation and benefits.

Qualifications

• 7+ years in infrastructure engineering with hands-on Kubernetes administration.
• Deep understanding of Kubernetes internals and cluster troubleshooting.
• Experience with container runtimes, Helm, GitOps, and declarative operations.
• Experience supporting GPU workloads on Kubernetes in lab/production.
• Strong Linux administration and data center networking knowledge.
• Ability to debug from symptom to root cause across node, pod, network, storage and control plane.
• Scripting in Python, Bash, or Go.

Responsibilities

• Build, administer, and troubleshoot Kubernetes platforms used for AI and data-intensive workloads.
• Diagnose failures across control plane components, kubelet, CNI, CSI, ingress, and scheduling.
• Support GPU-enabled Kubernetes environments, including device plugin behavior and drivers.
• Improve platform reliability through automation, configuration standards, upgrade planning, and validation gates.
• Investigate storage throughput, network policy, DNS, image pulls, autoscaling, and degraded node states.
• Collaborate with Linux, network, validation, and SRE teams to resolve cross-layer issues.
• Create reusable runbooks, dashboards, and health checks for day-2 operations.
• Contribute to platform hardening and tenant readiness.

Skills

Kubernetes admin

Linux admin

Python

Bash

Go

GPU workloads

Cluster troubleshooting

GitOps

Helm

Declarative ops

Networking basics

Tools

Kubeflow

Argo

Prometheus

Grafana

Loki

Service mesh

Bare-metal Kubernetes

High-performance storage

Job description

HCLTech is looking for a highly talented and self- motivated Senior Kubernetes Administrator – AI Infrastructure

to join it in advancing the technological world through innovation and creativity.

Job ID: 158106

Position Type: Full-time

Location: Remote

Role/Responsibilities

Engagement summary

The Candidate will provide senior Kubernetes platform engineering services for AI infrastructure environments supporting model development, distributed training, inference services, and shared platform operations. The role requires strong cluster troubleshooting ability plus pragmatic platform engineering skill in mixed bare-metal and data center environments.

What this Candidate will be doing

• Build, administer, and troubleshoot Kubernetes platforms used for AI and data-intensive workloads.
• Diagnose failures across control plane components, kubelet, CNI, CSI, ingress, service discovery, scheduling, node lifecycle, container runtime, and resource isolation.
• Support GPU-enabled Kubernetes environments, including device plugin behavior, driver dependencies, node health, and workload placement.
• Improve platform reliability through automation, standardized configuration, upgrade planning, and cluster validation gates.
• Investigate workload issues involving storage throughput, network policy, DNS, image pulls, autoscaling, pod eviction, and degraded node states.
• Partner with Linux, network, validation, and SRE teams to resolve complex cross-layer failures affecting AI services.
• Create reusable operational runbooks, dashboards, and health checks for day-2 support.
• Contribute to platform hardening, tenant readiness, and service-level objectives.

What we need to see

• 7+ years in infrastructure engineering, with deep hands-on Kubernetes administration experience.
• Strong operational understanding of Kubernetes internals and cluster troubleshooting.
• Experience with container runtimes, Helm, GitOps or declarative operations, and cluster lifecycle management.
• Experience supporting GPU workloads on Kubernetes in lab, validation, or production settings.
• Strong Linux administration foundation and understanding of data center network dependencies.
• Ability to debug issues from symptom to root cause across node, pod, network, storage, and control plane layers.
• Scripting and automation skill in Python, Bash, or Go.

Preferred experience

• Experience with Kubeflow, Argo, Prometheus, Grafana, Loki, or service mesh technologies.
• Familiarity with bare-metal Kubernetes and high-performance storage integration.
• Exposure to regulated or high-change-control production environments.

Pay and Benefits

Pay Range Minimum: $78,000/Annum

Pay Range Maximum: $148,000/Annum

HCLTech is an equal opportunity employer, committed to providing equal employment opportunities to all applicants and employees regardless of race, religion, sex, color, age, national origin, pregnancy, sexual orientation, physical disability or genetic information, military or veteran status, or any other protected classification, in accordance with federal, state, and/or local law. Should any applicant have concerns about discrimination in the hiring process, they should provide a detailed report of those concerns to [e-mail] for investigation.

Compensation and Benefits

A candidate’s pay within the range will depend on their work location, skills, experience, education, and other factors permitted by law. This role may also be eligible for performance-based bonuses subject to company policies. In addition, this role is eligible for the following benefits subject to company policies: medical, dental, vision, pharmacy, life, accidental death & dismemberment, and disability insurance; employee assistance program; 401(k) retirement plan; 10 days of paid time off per year (some positions are eligible for need-based leave with no designated number of leave days per year); and 10 paid holidays per year.

How You’ll Grow

At HCLTech, we offer continuous opportunities for you to find your spark and grow with us. We want you to be happy and satisfied with your role and to really learn what type of work sparks your brilliance the best. Throughout your time with us, we offer transparent communication with senior-level employees, learning and career development programs at every level, and opportunities to experiment in different roles or even pivot industries. We believe that you should be in control of your career with unlimited opportunities to find the role that fits you best.