Infrastructure Engineer

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., * 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.

• 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
• Certified Kubernetes Administrator (CKA)
• Certified Kubernetes Application Developer (CKAD), * 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.

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. xrbllit 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.

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.