Staff Network Engineer (AI Infrastructure)

As a Staff Network Engineer at vCluster Labs, you aren't just configuring switches; you are building the automation logic that configures them. AI Clouds run on InfiniBand and high-speed Ethernet fabrics that most teams still wire up by hand, one customer at a time. You will build the automation that turns that fabric into repeatable provisioning logic. You start in a small R&D group alongside our CTO and grow into owning this area as it becomes a core part of our platform.

What You'll Do

• Fabric automation: Design and build the systems that automatically provision and configure NVIDIA switches and InfiniBand fabrics, including integration with NVIDIA UFM. Manual, per-customer switch setup is the thing you are replacing.
• Network config management and sync: Build the control loop that keeps switch, VLAN, and VXLAN state consistent with what our platform intends, detects drift, and reconciles it safely in production.
• NAT gateway and L4 load balancing: Build the gateway and load balancing layer that tenant clusters depend on for connectivity, with failover designed in from day one rather than bolted on later.
• Scale and failure engineering: Define how our network layer behaves at large scale: BGP route table limits, convergence, failover, and what happens when a link, switch, or gateway dies under real AI workloads.
• Customer Zero for AI networking: Run your automation on real AI Cloud environments, bring back what breaks, and turn hard-won operational lessons into product behavior our customers never have to think about.
• Technical direction: Help decide what we build versus integrate with partner solutions, write design and requirements docs, and set the standards for how networking works across vCluster products.

What You Bring

• You have built network automation, not just operated networks: You have shipped software that configures switches, routers, or load balancers programmatically, ideally as part of a product or internal platform other teams relied on.
• NVIDIA networking experience: Hands-on work with NVIDIA UFM, NVIDIA Spectrum or Quantum switches, Cumulus Linux, or NVUE, including programming against their APIs.
• Deep fabric fundamentals: Strong command of InfiniBand, VLAN, VXLAN and EVPN, and BGP, including how they behave and fail at production scale.
• Production scale scars: You have run networks at real production scale, seen them break, and helped fix the root cause with automation rather than runbooks.
• Software engineering ability: You write production code in Go or Python, use version control and code review as a matter of course, and think of network config as code.

Bonus Points

• AI networking depth: Experience tuning fabrics for GPU training or inference workloads, such as RoCEv2, congestion control, rail-optimized topologies, or Spectrum-X.
• AI Cloud or hyperscaler background: You helped build network automation at a GPU cloud, hyperscaler, or large CDN.
• Load balancer and gateway internals: Experience building L4 load balancers or NAT gateways, including with eBPF/XDP or DPDK.
• Open source: Contributions to networking or Kubernetes projects such as SONiC, FRRouting, Cilium, or MetalLB.

Benefits

• Competitive Salary: A competitive compensation package, including equity.
• Premium Insurance: Health, dental, vision, and life insurance, including plans for you and eligible dependents (benefits vary depending on country).
• Flexible Working Schedule: Results matter more than clocking in and out at the same time every day.
• Workplace Flexibility: Very flexible about where you work, with willingness to adjust the work environment as life changes.