Senior Network Engineer — AI Infra & HPC Fabric Expert

Nscale; Houston (TX); On-site; USD 150,000 - 210,000; Full time

Benefits offered by this job

Competitive benefits package

Flexible paid time off

Parental leave

Retirement plan participation

Job summary

Nscale, a GPU cloud engineered for AI, is seeking a Senior Network Engineer to design and operate scalable InfiniBand and Ethernet fabrics for AI/ML workloads. You will own end-to-end network areas, mentor peers, and drive automation in a fast-paced cloud environment.

Join a team focused on high-performance, low-latency networking, cross-functional collaboration, and building scalable infrastructure for training and inference at scale.

Qualifications

• 8+ years of network engineering experience in HPC, AI, or hyperscale data centres.
• Deep RDMA/networking experience (InfiniBand, RoCE) for AI/HPC workloads.
• Strong design and operation of modern DC routing and control planes (BGP, EVPN-VxLAN).

Responsibilities

• Design, validate, and operate large-scale InfiniBand/RoCE and Ethernet fabric architectures.
• Develop and maintain network automation in a GitOps model using Python/Ansible.
• Drive incident response, root-cause analysis, and improve observability with telemetry and dashboards.
• Collaborate with deployment, DC operations, platform engineering, and vendors.
• Mentor engineers and contribute to site delivery across multiple locations.

Skills

Network engineering

RDMA networking

BGP EVPN VxLAN

Python

Ansible

Git

Firewall design

HPC/AI workloads

Network observability

Tools

Cumulus

Nokia

Arista EOS

OpenSM

UFM

Terraform

GitLab CI/GitHub Actions

Job description

Nscale, a GPU cloud engineered for AI, is seeking a Senior Network Engineer to design and operate scalable InfiniBand and Ethernet fabrics for AI/ML workloads. You will own end-to-end network areas, mentor peers, and drive automation in a fast-paced cloud environment.

Join a team focused on high-performance, low-latency networking, cross-functional collaboration, and building scalable infrastructure for training and inference at scale.