Staff Network Engineer (AI Infrastructure)

Accountabilities:: Design and develop automation systems for provisioning and configuring NVIDIA switches and InfiniBand network fabrics, including integration with NVIDIA UFM. Build network configuration management and synchronization systems that maintain consistent switch, VLAN, and VXLAN states, detect configuration drift, and safely reconcile differences in production. Develop NAT gateway and Layer 4 load-balancing capabilities to provide reliable connectivity for tenant clusters, with robust failover mechanisms. Define network architecture and behavior at scale, addressing BGP route table limits, convergence, failover, and resilience when links, switches, or gateways fail. Deploy and test networking automation in real AI cloud environments, identify operational challenges, and translate lessons learned into product improvements. Establish technical direction for networking capabilities, determining which solutions should be developed internally and which should integrate with partner technologies. Produce technical design documents, requirements, and engineering standards to guide networking development across the platform. Collaborate with engineering stakeholders to build scalable, reliable, and automated networking solutions for demanding AI workloads. Requirements: Proven experience in network automation, including developing software that programmatically configures switches, routers, or load balancers for production platforms or internal infrastructure. Hands-on experience with NVIDIA networking technologies such as NVIDIA UFM, Spectrum or Quantum switches, Cumulus Linux, or NVUE, including working with their APIs. Deep understanding of networking technologies and protocols, including InfiniBand, VLAN, VXLAN, EVPN, and BGP. Experience operating large-scale production networks, troubleshooting complex failures, and implementing automated solutions rather than relying solely on manual runbooks. Strong software engineering skills, with production coding experience in Go or Python. Familiarity with version control, code reviews, and infrastructure or network configuration managed as code. Additional assets: Experience optimizing network fabrics for GPU training or inference workloads, including RoCEv2, congestion control, rail-optimized topologies, or Spectrum-X. Background in network automation at a GPU cloud provider, hyperscaler, or large content delivery network. Experience developing Layer 4 load balancers or NAT gateways, including technologies such as eBPF/XDP or DPDK. Contributions to open-source networking or Kubernetes projects such as SONiC, FRRouting, Cilium, or MetalLB. Benefits: Competitive annual salary ranging from CAD $180,000 to $210,000 . Equity awards and potential bonus compensation. Health insurance coverage, including medical, dental, vision, and life insurance for employees and eligible dependents, subject to location. Flexible working schedule focused on results rather than fixed daily hours. Remote-first work environment with flexibility to adapt your workplace to changing needs. Retirement savings options, including RRSP plans in Canada. Country-specific benefits tailored to local employment arrangements.