Staff Network Engineer (AI Fabric, Datacenter and Edge Networking) - Radian Arc
Submer
WorldwideremotePosted 1 month ago
Skill Required
Staff-Network-EngineerAI-Fabric-NetworkingData-Center-NetworkingHPC-Network-EngineerNetwork-Infrastructure-EngineerSr.-Staff-Network-EngineerData-Center-Network-EngineerSenior-Network-Infrastructure-EngineerLead-Network-ArchitectLead-Network-EngineerData-Center-Network-Software-EngineerAI EngineerNetwork EngineernetworkingandAIMachine LearningtroubleshootingObservabilityEngineeringautomationdesigningsecuritydesignLinuxCloudDNSCryptographyFulltime
Key highlights
- Full time or Contract
- Start: Aug 2026
- Europe / Remote
- First dedicated networking role in the organization — Staff-level responsibilities with hands-on execution
- Deep expertise required in AI/GPU networking fabrics, RoCE, RDMA, and large-scale GPU cluster networking
- Strong automation skills in Python and/or Bash required
Role overview
Radian Arc is seeking a Staff Network Engineer to design, implement, and operate the network infrastructure powering its GPU cloud platform for cloud gaming and AI/ML applications inside telecommunications carrier networks. As the first dedicated networking role in the organization, this position combines Staff-level architectural ownership, technical direction, and cross-functional influence with hands-on execution across design, deployment, troubleshooting, automation, and operational improvement.
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
- Span 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, designing scalable GPU fabrics and ensuring predictable low-latency performance across distributed training and inference workloads
- Design large-scale RoCE and Ethernet fabrics and guide architecture decisions
- Ensure 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 that increase reliability, latency consistency, and operational maturity across the platform
- Operate at L6 / Staff level 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
- 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 including 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 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, 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 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
- 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, 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 collaborate closely with compute platform teams to ensure networking infrastructure is optimized for distributed training, distributed inference, and high-throughput AI workloads
- 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
Benefits
- Attractive compensation package reflecting your expertise and experience
- A great work environment characterised by friendliness, international diversity, flexibility, and a hybrid-friendly approach
- You'll be 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: Europe/ Remote
- Start: Aug 2026
- Type of Contract: Full time or Contract
- Radian Arc provides an infrastructure-as-a-service (IaaS) platform for running cloud gaming, artificial intelligence and machine learning applications inside telecommunication carrier networks
- Teams across the USA, Australia, Central Europe, Malaysia, Singapore and Japan offer telecom operators a GPU-based edge computing platform without the need for capital expenditure, facilitating low latency and improved economics for value-added services and the monetization of 5G investments
- This is the first dedicated networking role in the organization
- The position is intentionally hybrid: Staff-level technical direction combined with hands-on critical networking execution
- Our job titles may span more than one job level
- The actual base pay is dependent on a number of factors, such as transferable skills, work experience, business needs and market demands
- Radian Arc is committed to creating a diverse and inclusive environment and is proud to be an equal opportunity employer
- 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
- Originally posted on Himalayas