Network Engineer; AI Fabric, Datacenter and Edge Networking; Radian Arc

Location & work modality:
Remote Type of

Contract:

Full time or Contract

We’re specialists in outcome-optimized AI infrastructure - deploying, orchestrating and monetizing GPU compute where data, users and demand actually meet: inside telco networks, at the edge, and in core data centers.

Not a generic AI platform. Not a consultancy. We’re the bridge between raw silicon and real-world results.

Design, implement, and operate the network infrastructure powering the GPU cloud platform, including high-performance AI fabrics as well as classical datacenter networking components such as routing, security, and external connectivity. This role spans both high-performance east-west networking for distributed AI workloads and north-south connectivity, security, and inter-datacenter transport. As the first dedicated networking role in the organization, the Staff Network Engineer combines Staff-level architectural ownership, technical direction, and cross-functional influence with hands‑on execution across design, deployment, troubleshooting, automation, and operational improvement.

The Staff Network Engineer owns the long‑term technical direction and operational strategy for Radian Arc ’s AI interconnect networks, designing scalable GPU fabrics and ensuring predictable low‑latency performance across distributed training and inference workloads. The role includes designing large‑scale RoCE and Ethernet fabrics, guiding architecture decisions, and ensuring operational excellence across global deployments, from hyperscale datacenters to smaller edge locations.

You will collaborate closely with platform, compute, storage, observability, and operations teams to ensure networking is deeply integrated into the overall infrastructure architecture. This role also acts as the senior escalation point for complex networking incidents, driving deep technical investigations and systemic improvements that increase reliability, latency consistency, and operational maturity across the platform. Because this is currently the primary networking role in the company, the position is intentionally hybrid: you are expected to operate at L6 / Staff in terms of technical direction, standards, cross‑team influence, and long‑term design, while also directly executing critical networking work that, in a larger organization, would be distributed across multiple engineers.

We expect to hire more than one person for this role so providing you have experience in designing AI Infrastructure networking solutions at scale.

Design and operate high-performance GPU networking fabrics supporting distributed AI workloads. Architect large‑scale RoCE fabrics optimized for distributed training and inference. Optimize network performance for GPU communication patterns and east‑west traffic.

Design fabric topologies such as:

• Leaf-spine
• Fat-Tree
• Rail architectures
• Multi-plane

Implement high-performance networking technologies including:

• RDMA
• RoCE
• High‑bandwidth east‑west fabrics
• Spectrum-X

Collaborate with compute teams to support distributed training frameworks and GPU communication libraries. Define reference architectures and design principles for AI fabrics so future deployments follow reusable standards rather than one‑off implementations. Evaluate architectural trade‑offs across performance, resilience, cost, operability, and deployment speed, and make clear recommendations to stakeholders.

Design and operate Layer‑2 and Layer‑3 datacenter networks. Implement scalable routing architectures based on BGP and ECMP. Design tenant network isolation mechanisms across multi‑tenant environments.

Implement and maintain:

• Network bridges
• Routing stacks
• Overlay…