Infrastructure Engineer

HCL Technologies Limited; California (MO); On-site; USD 120,000 - 180,000; Full time

Benefits offered by this job

401(k) retirement plan

Paid time off (PTO)

Paid holidays

Medical, dental, vision insurance

Job summary

HCL Technologies Limited is seeking an experienced AI Infrastructure Engineer (L3) to design, deploy, optimize, and support high-performance GPU-based AI infrastructure. You will manage large GPU clusters, support AI training/inference workloads, and drive platform reliability.

Applicants should have deep expertise in NVIDIA GPU platforms, Kubernetes, HPC environments, and cloud-native AI technologies. Collaboration with cloud, data science, and SRE teams is essential.

Qualifications

• Bachelor's degree in CS/Engineering or related field.
• 8-12 years of infrastructure/platform engineering experience.
• 4-6 years supporting AI/ML environments and GPU-based platforms.
• Experience operating production-scale AI infrastructure.

Responsibilities

• Deploy and manage NVIDIA GPU infrastructure and AI accelerator platforms.
• Administer Kubernetes GPU clusters with NVIDIA GPU Operator.
• Install CUDA, cuDNN, TensorRT, firmware and drivers.
• Manage Ceph, Lustre, BeeGFS, and NFS storage.
• Support InfiniBand, RDMA, RoCE, NVLink and other high-speed networking.
• Optimize Linux environments for AI and HPC workloads.
• Support Kubeflow, MLflow, Ray, and Slurm.
• Implement infrastructure as code with Terraform, Helm, and GitOps.
• Monitor with Prometheus, Grafana, NVIDIA DCGM and OpenTelemetry.
• Lead RCA and resolve GPU, networking, storage, and platform issues.
• Collaborate with cloud, data science, MLOps, SRE, and engineering teams.

Skills

NVIDIA GPU platforms

GPU cluster administration

Kubernetes & cloud-native tech

CUDA & TensorRT

Distributed training frameworks

Linux performance tuning

Terraform & Helm

ArgoCD & automation

MLOps & AI infra

Troubleshooting & production support

Education

Bachelor's Degree in CS/Engineering or related field

Tools

NVIDIA GPU Operator

Ceph

Lustre

BeeGFS

NFS

Prometheus

Grafana

OpenTelemetry

Kubeflow

MLflow

Ray

Slurm

GitOps tools

Terraform

Helm

Job description

HCLTech is a global technology company with over 220,000 professionals across 60 countries, delivering industry-leading capabilities in Digital, Engineering, Cloud, and AI. We help enterprises accelerate innovation through cutting-edge technologies and world-class talent.

Job Summary

We are seeking an experienced AI Infrastructure Engineer (L3) to design, deploy, optimize, and support high-performance AI and Machine Learning infrastructure. The ideal candidate will have deep expertise in GPU platforms, Kubernetes, HPC environments, distributed systems, and cloud-native AI technologies. This role involves managing large-scale GPU clusters, supporting AI training and inference workloads, troubleshooting complex infrastructure issues, and driving platform reliability.

Key Responsibilities

• Deploy and manage NVIDIA GPU infrastructure (A100, H100, L40) and AI accelerator platforms.
• Administer Kubernetes GPU clusters using NVIDIA GPU Operator and related technologies.
• Install and maintain CUDA, cuDNN, TensorRT, firmware, and driver stacks.
• Manage high-performance storage solutions such as Ceph, Lustre, BeeGFS, and NFS.
• Support InfiniBand, RDMA, RoCE, NVLink, and other high-speed networking technologies.
• Optimize Linux environments (RHEL, Ubuntu, Rocky Linux) for AI and HPC workloads.
• Support AI orchestration platforms including Kubeflow, MLflow, Ray, and Slurm.
• Implement Infrastructure as Code using Terraform, Helm, and GitOps tools.
• Monitor platform performance with Prometheus, Grafana, NVIDIA DCGM, and OpenTelemetry.
• Lead root cause analysis (RCA) and resolve critical GPU, networking, storage, and platform issues.
• Collaborate with cloud, data science, MLOps, SRE, and engineering teams to deliver scalable AI platforms.

Required Skills

• Strong experience with NVIDIA GPU platforms and GPU cluster administration.
• Expertise in Kubernetes, containerization, and cloud-native technologies.
• Hands-on experience with CUDA, TensorRT, NCCL, DeepSpeed, Horovod, and distributed training.
• Strong Linux administration and performance tuning skills.
• Experience with Terraform, Helm, ArgoCD, and automation frameworks.
• Knowledge of AI infrastructure, MLOps, and large-scale distributed systems.
• Excellent troubleshooting, debugging, and production support experience.

Preferred Certifications

• NVIDIA Certified Associate – AI Infrastructure
• NVIDIA Base Command Manager Certification
• AWS Solutions Architect Associate

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.

Disclaimer

HCL 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.