Senior AI Network Engineer - AI Infrastructure

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.

Ready to make a move? Get in touch and apply today!

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