AI Infrastructure Engineer - GPU & Kubernetes

HCLTech; California (MO); On-site; USD 150,000 - 210,000; Full time

Benefits offered by this job

Medical Insurance

Dental Insurance

Vision Insurance

401(k) Retirement Plan

Paid Time Off and Holidays

Job summary

HCLTech is seeking an experienced AI Infrastructure Engineer (L3) to design, deploy, and optimize large-scale GPU-based AI infrastructure. The role covers GPU clusters, CUDA/TensorRT stacks, storage, and high-speed networking across Linux environments in cloud-native contexts.

Ideal candidates will have extensive Kubernetes experience, proficiency with Terraform/Helm/ArgoCD, and a track record of production-grade AI platforms.

Qualifications

• Bachelor's Degree in Computer Science, Engineering, or a related field.
• 8-12 years of Infrastructure or Platform Engineering experience.
• 4-6 years supporting AI/ML environments and GPU-based platforms.
• Experience operating production-scale AI infrastructure.
• Strong Linux administration and performance tuning skills.
• Experience operating Kubernetes and cloud-native technologies.
• Hands-on experience with Terraform, Helm, ArgoCD, and automation frameworks.

Responsibilities

• Deploy and manage NVIDIA GPU infrastructure and AI accelerator platforms.
• Administer Kubernetes GPU clusters using NVIDIA GPU Operator.
• Install and maintain CUDA, cuDNN, TensorRT, firmware, and driver stacks.
• Manage high-performance storage such as Ceph, Lustre, BeeGFS, and NFS.
• Support InfiniBand, RDMA, RoCE, NVLink, and other high-speed networking.
• Optimize Linux environments for AI and HPC workloads.
• Support AI orchestration platforms like Kubeflow, MLflow, Ray, and Slurm.
• Implement Infrastructure as Code using Terraform, Helm, and GitOps.
• Monitor platform performance with Prometheus, Grafana, NVIDIA DCGM, and OpenTelemetry.
• Lead root cause analysis and resolve GPU, networking, storage, and platform issues.
• Collaborate with cloud, data science, MLOps, SRE, and engineering teams to deliver scalable AI platforms.

Skills

NVIDIA GPU platforms

Kubernetes

CUDA

TensorRT

HPC environments

Linux performance tuning

Terraform

Helm

ArgoCD

OpenTelemetry

Prometheus

NVIDIA DCGM

Education

Bachelor's Degree in Computer Science or Engineering

Tools

NVIDIA GPU Operator

Kubernetes

Terraform

Helm

ArgoCD

GitOps

Prometheus

Grafana

NVIDIA DCGM

Job description

HCLTech is seeking an experienced AI Infrastructure Engineer (L3) to design, deploy, and optimize large-scale GPU-based AI infrastructure. The role covers GPU clusters, CUDA/TensorRT stacks, storage, and high-speed networking across Linux environments in cloud-native contexts.

Ideal candidates will have extensive Kubernetes experience, proficiency with Terraform/Helm/ArgoCD, and a track record of production-grade AI platforms.