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# Infrastructure Engineer

- **Company:** HCL America Inc.
- **Location:** Santa Clara, CA, United States
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Ubuntu (Operating System), Cloud Computing, Cloud Engineering, Computer Clusters, Nvidia CUDA, Software Debugging, Linux, Distributed Computing Environment, Distributed Systems, Firmware, InfiniBand, Linux System Administration, Performance Tuning, Remote Direct Memory Access, Red Hat Enterprise Linux, Reliability Engineering, Prometheus, AI Infrastructure, Ceph (Software), High Performance Computing, DeepSpeed, System Availability, Grafana, Multi-Agent Systems, cuDNN, Containerization, Kubernetes, Information Technology, Slurm, Machine Learning Operations, TensorRT, Hardware Infrastructure, Terraform
- **Published:** October 13, 2026
- **Apply:** https://www.juju.com/job/2_163946225

## About the Role

* 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.

## Description

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.