Network Architect (AI Infrastructure)

Location: Remote in the United States or United Kingdom; full working overlap with US Pacific time required.

Company

hirify.global operates an AI infrastructure platform that routes inference requests through GPU clusters, data centers, cloud environments, and partner capacity.

What you will do

• Own the end-to-end network architecture and multi-year roadmap across data center fabrics, backbone, edge, cloud, and hybrid connectivity.
• Design and build GPU cluster networks using spine-leaf fabrics, 400G/800G Ethernet, RoCEv2, lossless transport, congestion control, and InfiniBand.
• Optimize multi-region interconnect, transit, peering, anycast, traffic steering, DDoS protection, and customer-facing latency.
• Connect hyperscalers, bare-metal providers, and colocation sites through VPCs, VPNs, and private interconnects.
• Establish observability, change management, incident response, on-call practices, capacity planning, procurement, and network-as-code automation.
• Set network standards, review designs, mentor engineers, define the hiring plan, and manage vendor, carrier, hardware, optics, and interconnect relationships.

Requirements

• 15+ years in network engineering and architecture, including at least 5 years as design authority for large-scale production networks at a cloud provider, hyperscaler, CDN, HPC/AI infrastructure company, or carrier.
• Hands-on experience designing, configuring, troubleshooting, and building data center, backbone, and cloud networks from the ground up.
• Deep current expertise in spine-leaf Clos fabrics, EVPN/VXLAN, BGP at scale, 400G/800G Ethernet, RoCEv2, PFC, ECN, DCQCN, lossless Ethernet, and InfiniBand.
• Strong backbone and edge experience with multi-region interconnect, transit, peering, anycast, traffic engineering, and DDoS mitigation, including measurable customer-facing latency improvements.
• Cloud and hybrid networking across at least two hyperscalers plus bare-metal or colocation environments, including VPCs, private interconnects, and VPNs at scale.
• Experience building network operations, observability, change management, incident response, on-call practices, and capacity forecasting and procurement processes.
• Working practice with Python or Go, infrastructure as code for network configuration, CI-style validation, and streaming telemetry.
• Demonstrated use of AI tooling for network design, configuration and automation code, telemetry analysis, and documentation.
• Experience hiring and leading high-performance engineering teams, setting standards, and leading through influence without direct reports.
• Strong ownership and comfort working in a fast-moving, ambiguous environment.
• Based in, or able to maintain full working overlap with, US Pacific time.

Nice to have

• Experience networking large GPU clusters for AI inference or training, including NVIDIA Spectrum-X, Quantum InfiniBand, NCCL tuning, or GPUDirect RDMA.
• Experience with SONiC, Cumulus, Arista EOS, Junos, NVIDIA Cumulus/Spectrum, Ultra Ethernet, 800G/1.6T optics, co-packaged optics, or emerging fabric technologies.
• Experience running peering and transit for latency-sensitive products, including ASN management, route optimization, and IXP presence.
• Experience with eBPF, DPDK, SmartNICs/DPUs, or kernel-bypass networking.
• Startup or scale-up experience building a network function from zero.
• Public contributions such as RFCs, open-source network tooling, conference talks, or published post-mortems.

Culture & Benefits

• Remote-first work with twice-yearly in-person company retreats.
• Core collaboration hours with flexible scheduling outside those blocks.
• Fast release cycles followed by planned downtime and recovery.
• Paid vacation, sick days, public holidays, maternity, paternity, and caregiver leave.
• Meaningful stock options and flexible ownership of the work schedule.