Staff Network Engineer (AI Fabric, Datacenter and Edge Networking) - Radian Arc
Radian Arc
WorldwideremotePosted 13 days ago
Skill Required
Network-EngineerStaff-Network-EngineerAI-Infrastructure-EngineerData-Center-Network-EngineerNetwork-ArchitectSenior-Network-Infrastructure-EngineerNetwork-Infrastructure-EngineerLead-Network-EngineerAI EngineerNetwork EngineernetworkingandAItroubleshootingObservabilityEngineeringautomationdesigningsecuritydesignLinuxCloudDNSCryptographyFulltime
Key highlights
- Remote work modality
- Staff/L6 experience level
- Requirement: Deep expertise in AI Fabric/GPU networking
- Contract: Full time or Contract
- Benefit: Hybrid-friendly, diverse environment
Role overview
Radian Arc is a specialist in outcome-optimized AI infrastructure, focusing on deploying, orchestrating, and monetizing GPU compute within telco networks, at the edge, and in core data centers. They serve as the bridge between raw silicon and real-world results, rather than acting as a generic AI platform or consultancy. The Staff Network Engineer will be the first dedicated networking role in the organization, combining Staff-level architectural ownership and technical direction with hands-on execution. This hybrid role is responsible for the long-term technical direction and operational strategy for AI interconnect networks, designing scalable GPU fabrics to ensure predictable low-latency performance across distributed training and inference workloads.
Responsibilities
- 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.
- Manage both high-performance east-west networking for distributed AI workloads and north-south connectivity, security, and inter-datacenter transport.
- Own the long-term technical direction and operational strategy for Radian Arc’s AI interconnect networks.
- Design large-scale RoCE and Ethernet fabrics, guiding architecture decisions and ensuring operational excellence across global deployments, from hyperscale datacenters to smaller edge locations.
- Collaborate closely with platform, compute, storage, observability, and operations teams to ensure networking is deeply integrated into the overall infrastructure architecture.
- Act as the senior escalation point for complex networking incidents, driving deep technical investigations and systemic improvements.
- Operate at L6 / Staff level in terms of technical direction, standards, cross-team influence, and long-term design while directly executing critical networking work.
- 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, and Multi-plane.
- Implement high-performance networking technologies including RDMA, RoCE, High-bandwidth east-west fabrics, and Spectrum-X.
- Collaborate with compute teams to support distributed training frameworks and GPU communication libraries.
- Define reference architectures and design principles for AI fabrics to ensure future deployments follow reusable standards.
- 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, and overlay networking systems.
- Maintain north-south ingress/egress routing and traffic management.
- Define standards and reusable patterns for segmentation, routing, and overlay integration across platform deployments.
- Deploy and maintain north-south security infrastructure.
- Implement WAF and application-layer protections.
- Integrate security controls with platform services.
- Design and operate private interconnects between datacenters.
- Implement and maintain dark fiber ring architectures.
- Operate high-capacity WAN connectivity between regions.
- Integrate datacenter fabrics into a global backbone network.
- Define scalable design principles for backbone evolution, inter-site routing, redundancy, and failure-domain isolation.
- Lead end-to-end engineering delivery of networking infrastructure, from design and lab validation 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.
- Establish deployment standards, validation criteria, rollback approaches, and acceptance patterns.
- Own operational performance and reliability of networking infrastructure.
- Drive automation for provisioning, configuration management, monitoring, and lifecycle management.
- Improve day-2 operations through automation and operational tooling.
- Lead incident response and root-cause analysis for major network events.
- Define and track SLAs, SLOs, and reliability metrics.
- Translate major incidents and operational pain points into durable standards, design changes, and long-term architectural improvements.
- 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.
- Provide technical leadership across infrastructure initiatives.
- Communicate architectural decisions, trade-offs, and risks clearly to stakeholders.
- Influence the long-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.
Requirements
- Strong hands-on experience designing and operating large-scale datacenter networks.
- Expert knowledge of modern networking protocols including BGP, OSPF, ECMP, and EVPN / VXLAN.
- Proven experience operating high-speed Ethernet networks in production environments.
- Experience operating NVIDIA / Mellanox networking platforms.
- Deep expertise in designing and operating networking fabrics optimized for large-scale GPU clusters and distributed AI workloads.
- 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.
- Experience tuning RoCE fabrics for large-scale GPU clusters.
- Strong knowledge of RDMA transport behavior and failure modes.
- Practical experience implementing and tuning PFC and ECN for congestion management.
- Understanding of GPU collective communication patterns such as all-reduce, all-gather, broadcast, reduce-scatter, and their impact on east-west network traffic.
- Experience designing rail-optimized GPU networking fabrics for distributed training and inference clusters.
- Familiarity with diagnosing performance issues related to NCCL stalls, RDMA congestion, Fabric hotspots, and Packet loss impacting distributed training.
- Understanding of how networking performance affects distributed AI frameworks such as PyTorch and TensorFlow.
- Ability to debug complex cross-layer issues spanning hardware, firmware, kernel networking, and distributed application communication layers.
- Strong knowledge of networking hardware, optics, and high-speed interconnects.
- Experience designing network observability systems.
- Strong ability to act as the senior escalation point for ambiguous, high-impact, and multi-domain technical issues.
- Strong automation skills using Python and/or Bash.
- Experience applying software engineering practices to infrastructure automation.
- Experience building reusable tooling, standards, or validation approaches that increase leverage across teams.
- Proven ability to lead complex technical initiatives across teams.
- Comfortable collaborating across engineering, operations, and vendors.
- Strong systems-level thinking balancing performance, reliability, scalability, and operational cost.
- Demonstrated ability to set architectural direction and drive adoption of engineering standards across an organization.
- Proven ability to lead through technical influence across multiple teams and domains, without relying on formal people management authority.
- Strong mentoring capability and ability to raise the technical level of adjacent engineering teams.
- Able to balance short-term execution needs with long-term platform design, operational sustainability, and cost efficiency.
Nice to have
- Experience owning both architecture and direct implementation in lean or fast-scaling environments is strongly preferred.
Benefits
- Attractive compensation package reflecting your expertise and experience.
- A great work environment characterised by friendliness, international diversity, flexibility, and a hybrid-friendly approach.
- Part of a fast-growing scale-up with a mission to make a positive impact, offering an exciting career evolution.
Additional details
- Location & work modality: Remote
- Type of Contract: Full time or Contract
- Technical Stack - Datacenter Networking: BGP, EVPN / VXLAN, ECMP, VLAN / VRF, OVS / OVN, Linux networking, BlueField DPU
- Technical Stack - Routing & Control Plane: VyOS, BGP-based routing architectures, ECMP fabrics
- Technical Stack - Security: Citrix NetScaler / WAF, DDoS protection
- Technical Stack - Transport & Backbone: Dark fiber, Metro fiber rings, DWDM transport, 100–1600G optical networking
- Technical Stack - AI Networking: RDMA, RoCE, GPU fabrics, Large-scale east-west compute networking, Congestion control
- The company expects to hire more than one person for this role; applicants with experience in designing AI Infrastructure networking solutions at scale are encouraged to apply even if they do not match the full scope of the position.
- Actual base pay is dependent on factors such as transferable skills, work experience, business needs and market demands.
- Radian Arc is an equal opportunity employer committed to a diverse and inclusive environment.