[Hiring] Staff Network Engineer @vCluster Labs

Role Description

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.

• Fabric automation: You will 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: You will 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: You will 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: You will 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: You will 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: You will help decide what we build versus integrate with partner solutions, write the design and requirements docs, and set the standards for how networking works across vCluster products.

Qualifications

• 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.

Requirements

• 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: We offer 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: You have a doctor’s appointment or need to head to the supermarket to get groceries at 2pm? We won’t have an issue with that. To us, results matter more than clocking in and out at the same time every day.
• Workplace Flexibility: We’re very flexible about where you work. We know things can change in life and we’re happy to adjust the work environment for you along the way.