Staff Networking Platform Engineer – AI Cloud Networking

Themuralgroup; United States; Remote; USD 270,000 - 462,000; Full time

Job summary

The muralgroup is a late-stage AI cloud company backed by NVIDIA, building a managed Kubernetes platform that turns large fleets of bare-metal GPU compute into dedicated, isolated clusters for customers running AI training and inference. This remote US role is based in Dallas, San Francisco or New York City, with remote work now and a hybrid plan later.

You will own networking across the platform—from Kubernetes cluster networking down through the data center fabric and GPU interconnect—driving

Qualifications

• Deep networking with focus on TCP/IP, BGP, and segmentation.
• Bare-metal leaf-spine data center networks with VLANs/EVPN/VXLAN.
• Kubernetes and Linux networking, CNI behavior and network policy.
• Kubernetes controllers, operators or CRs in Go, with GitOps.
• Multitenant infrastructure or managed Kubernetes products.
• Securing networks that run customer workloads.

Responsibilities

• Define how networking features are requested, provisioned, changed, observed and removed
• Automate tenant and node network lifecycles with Kubernetes-native tooling, including safe recovery from partial failures
• Manage BGP, routing policy, VLANs and overlays, plus VIPs, load balancers and public IPs, through fabric APIs
• Automate GPU networking (NVL72, InfiniBand, RoCE, GPUDirect) and validate isolation and performance
• Own IPAM and inventory integration so intended config, applied state and inventory stay in sync
• Set segmentation and traffic policy with security engineering, and standards enforced through GitOps and drift reconciliation
• Own network telemetry, troubleshooting and incident response

Skills

Deep networking

Bare-metal nets

Kubernetes networking

Kubernetes controllers

Multitenant infra

Network security

Job description

The muralgroup is a late-stage AI cloud company backed by NVIDIA, building a managed Kubernetes platform that turns large fleets of bare-metal GPU compute into dedicated, isolated clusters for customers running AI training and inference. This remote US role is based in Dallas, San Francisco or New York City, with remote work now and a hybrid plan later.

You will own networking across the platform—from Kubernetes cluster networking down through the data center fabric and GPU interconnect—driving