Staff Networking Platform Engineer, Infrastructure

Mural Group

United States

Remote

USD 270,000 - 462,000

Full time

2 days ago
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Job summary

Mural Group is seeking a senior networking engineer to own the networking across a cloud AI platform. You will design and automate Kubernetes-native networking, manage data-center fabric, and ensure isolation and performance for GPU workloads.

You will lead end-to-end networking features, from provisioning to monitoring, with a focus on multitenant, secure, and performant infrastructure. This role is remote (US) with base in major cities and near-term hybrid plans.

Qualifications

  • Deep networking: TCP/IP, BGP, routing policy, ECMP, segmentation and interconnects.
  • Production ownership of multi-tenant data center networks with VLANs/EVPN/VXLAN.
  • Kubernetes and Linux networking: CNI behavior, network policy.
  • Kubernetes controllers, operators or CRs in Go with GitOps and controlled rollouts.
  • 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 and safe recovery.
  • Manage BGP, routing policy, VLANs and overlays, plus VIPs, load balancers and public IPs.
  • Automate GPU networking and validate isolation and performance.
  • Own IPAM and inventory integration to keep config and inventory in sync.
  • Set segmentation and traffic policy with security engineering and GitOps standards.
  • Own network telemetry, troubleshooting and incident response.

Skills

TCP/IP
BGP
routing policy
ECMP
segmentation
interconnects
Kubernetes
CNI
Cilium
GitOps
Go
networking for multitenant infra

Tools

Kubernetes
Linux networking
CNI
Go
GitOps

Job description

Location

Remote (US). Must be based in Dallas, San Francisco or New York City. Remote for now, with hybrid planned further down the road.

Pay
  • L6 (Staff): $270,400-365,800
  • L7 (Sr. Staff): $341,400-461,800

Compensation is not an issue for the right person. The role pays nearly all cash: the bonus is folded into base, and there is an equity component on top.

A late-stage AI cloud company backed by NVIDIA, with a valuation in the billions, runs AI compute out of data centers around the world. It is now 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 role owns networking across the whole platform, from Kubernetes cluster networking down through the data center fabric and GPU interconnect, and turns customer connectivity, isolation and performance needs into managed platform features.

What you'll do
  • 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
What you bring
  • Deep networking: TCP/IP, BGP, routing policy, ECMP, segmentation, interconnects
  • Production ownership of bare-metal leaf-spine data center networks with VLANs, VRFs and EVPN/VXLAN
  • Kubernetes and Linux networking: CNI behavior, Cilium or similar, network policy
  • Kubernetes controllers, operators or custom resources in Go, with GitOps and controlled rollouts
  • Multitenant infrastructure or managed Kubernetes products
  • Securing networks that run customer workloads
Nice to have

Netris, UFM or NetBox; NVIDIA AI networking (InfiniBand, Spectrum-X, RDMA, RoCE, congestion control); networking for large GPU clusters, including multi-site

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