Senior AI Network Engineer - AI Infrastructure

Hamilton Barnes Associates Limited; United States; On-site; USD 220,000 - 350,000; Full time

Benefits offered by this job

Annual bonus

Equity opportunities

Flexible working arrangements

Career progression

Job summary

Hamilton Barnes Associates Limited is seeking a Senior AI Network Engineer to design, deploy, and optimize networking for large-scale GPU clusters driving AI workloads. You will build low-latency Ethernet/InfiniBand fabrics, configure NVIDIA Spectrum switches, and implement automation with Python, Ansible, and IaC to boost performance and reliability across HPC environments.

Collaborate with platform, storage, Kubernetes, and infra teams to maximize cluster performance, reliability, and scalable

Qualifications

• 5+ years in Network Engineering for large-scale data centres, cloud, or AI infrastructure.
• Deep knowledge of spine-leaf architectures and data centre networks.
• Hands-on with NVIDIA Spectrum switches and Cumulus Linux.
• Experience with Ethernet fabrics for AI/HPC workloads and modern routing.
• Scripting in Python/Bash and IaC, plus automation/telemetry experience.

Responsibilities

• Design, deploy, and operate high-performance AI networking for large GPU clusters.
• Build low-latency Ethernet/InfiniBand fabrics for distributed AI training/inference.
• Configure NVIDIA Spectrum, Cumulus Linux, and spine-leaf architectures.
• Optimize performance with RDMA/RoCE/GPUDirect RDMA and NCCL.
• Collaborate with platform/storage/Kubernetes teams to maximize cluster performance.

Skills

Spine-leaf networking

NVIDIA Spectrum switches

Cumulus Linux

RDMA / RoCE / InfiniBand

BGP / EVPN-VXLAN / MLAG

Linux systems / scripting

Infrastructure-as-Code

Network telemetry

GPU infrastructure

Tools

Python

Bash

Ansible

Kubernetes

Git

Job description

Looking for a role with plenty of growth opportunities?

Join one of North America's fastest-growing AI infrastructure providers, delivering large-scale GPU cloud platforms for AI training, fine-tuning, and inference workloads. Backed by significant investment and advanced infrastructure expertise, the organization builds high-performance AI environments powered by NVIDIA GPUs, high-speed networking, storage, and Kubernetes.

This company is seeking a Senior AI Network Engineer to design, deploy, and optimize networking infrastructure for large-scale GPU clusters. The role offers the opportunity to solve complex HPC and AI networking challenges while supporting low-latency, high-bandwidth platforms built for next-generation AI workloads.

Responsibilities:

• Design, deploy, and operate high-performance AI networking infrastructure supporting large-scale GPU clusters.
• Build and optimise low‑latency Ethernet and InfiniBand fabrics for distributed AI training and inference workloads.
• Configure and support NVIDIA Spectrum switches, Cumulus Linux, and modern spine‑leaf network architectures.
• Optimise network performance for RDMA, RoCE, GPUDirect RDMA, NCCL, and large‑scale distributed training.
• Collaborate with platform, storage, Kubernetes, and infrastructure teams to maximise cluster performance and reliability.
• Develop network automation using Infrastructure‑as‑Code, CI/CD, and configuration management tools.
• Implement monitoring, telemetry, and observability across AI networking environments.
• Troubleshoot complex networking, hardware, and distributed systems issues across production GPU infrastructure.
• Support capacity planning, network scaling, and future infrastructure expansion.

Skills / Must Have:

• 5+ years of experience in Network Engineering supporting large-scale data centre, cloud, HPC, or AI infrastructure environments.
• Strong knowledge of spine‑leaf networking and large‑scale data centre architectures.
• Hands‑on experience with NVIDIA Spectrum switches and Cumulus Linux.
• Deep understanding of Ethernet fabrics supporting AI and HPC workloads.
• Experience with RoCE, RDMA, InfiniBand, BGP, EVPN‑VXLAN, MLAG, and modern routing protocols.
• Experience supporting GPU infrastructure and distributed AI training environments.
• Strong Linux systems knowledge and scripting experience using Python, Bash, or Ansible.
• Experience with automation, Infrastructure‑as‑Code, and network telemetry platforms.

Desirable Skills:

• Experience supporting NVIDIA H100, H200, B200, or Blackwell GPU deployments.
• Knowledge of NCCL, CUDA networking optimisation, GPUDirect RDMA, and distributed AI workloads.
• Experience with Kubernetes networking and cloud‑native infrastructure.
• Familiarity with storage networking technologies including VAST, Weka, or BeeGFS.
• Background working within hyperscalers, GPU cloud providers, AI infrastructure companies, or HPC environments.
• Experience deploying multi‑thousand GPU clusters.

Benefits:

• Competitive salary with annual bonus and equity opportunities.
• Opportunity to help build one of North America's fastest-growing AI infrastructure platforms.
• Work with cutting‑edge NVIDIA GPU technology and hyperscale networking environments.
• High-impact engineering role with significant technical ownership.
• Collaborative engineering culture with minimal bureaucracy.
• Flexible working arrangements and excellent career progression.

Salary:

• $220,000 – $350,000 Base Salary