Design tenant network isolation mechanisms across multi-tenant environments. Linux networking stacks Linux networking 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 consultancy. 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 general 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?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 please do not hesitate to apply if your experience does not match the full scope of the position.





AI Fabric & HPC Networking 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?Implement high-performance networking technologies including: 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?offs across performance, resilience, cost, operability, and deployment speed, and make clear recommendations to stakeholders.

Datacenter

Networking 3 datacenter networks. Design tenant network isolation mechanisms across multi?Network bridges Overlay networking systems Define standards and reusable patterns for segmentation, routing, and overlay integration across platform deployments. Linux networking stacks Integrate security controls with platform services Citrix NetScaler / Citrix WAF API and proxy gateway protection Datacenter Networking Integrate datacenter fabrics into a global backbone network Lead end?to?end engineering delivery of networking infrastructure, from design and labvalidation to production deployment Validate network BOMs together with procurement and deployment teams Provide detailed input into datacenter layouts and rack elevations Drive capacity planning, performance modeling, and scaling strategies Ensure network changes are executed safely with minimal customer impact Act as both the architectural owner and the practical execution lead for critical network initiatives during the build?out phase of the networking function Establish deployment standards, validation criteria, rollback approaches, and acceptance patterns that future engineers and teams can reuse Own operational performance and reliability of networking infrastructure Configuration management Monitoring cause analysis for major network events Establish measurable benchmarks for reliability, latency consistency, operability, and recovery behavior across network deployments.

Work closely with infrastructure, platform, SRE, compute, storage,



observability, and datacenter operations teams. term platform networking roadmap and architecture. Act as the primary networking design authority across the organization, guiding adjacent teams on how networking constraints and capabilities should shape platform decisions. Raise the technical bar by mentoring engineers in adjacent domains and helping build the future networking function.

Datacenter Networking

Linux networking Routing & Control Plane Citrix NetScaler / WAF G optical networking AI Networking west compute networking Congestion control scale datacenter networks Expert knowledge of modern networking protocols including: speed Ethernet networks in production environments Experience operating NVIDIA / Mellanox networking platforms Advanced AI Fabric Networking Expertise The candidate should have deep expertise in designing and operating networking fabrics optimized for large?This includes a strong understanding of GPU communication patterns and the networking requirements of distributed training and inference systems. Deep understanding of NCCL communication patterns and their impact on network topology and performance. west network traffic. optimized GPU networking fabrics for distributed training and inference clusters. Familiarity with diagnosing performance issues related to: Packet loss impacting distributed training Understanding of how networking performance affects distributed AI frameworks such as PyTorch and TensorFlow.

The candidate should also be able to collaborate closely with compute platform teams to ensure that networking infrastructure is optimized for distributed training, distributed inference, andhigh?Kernel networking Strong knowledge of networking hardware, optics, and high?Experience designing network observability systems. Strong ability to act as the senior escalation point for ambiguous, high?Strong automation skills using Python and/or Bash.

Experience applying software engineering practices to infrastructure automation. level thinking balancing performance, reliability, scalability, and operational cost. Able to balance short?term execution needs with long?A great work environment characterised by friendliness, international diversity, flexibility, and a hybrid?All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, veteran status, or any other protected category under applicable law. #

📌 Staff Network Engineer (Ai Fabric, Datacenter And Edge Networking) - Radian Arc (Melilla)
🏢 Radian Arc
📍 Melilla