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Runware

Generative AI platform with fast inference

Network Architect

Network Engineering & AdministrationUpdated on Nov 10
Full-timePalo Alto, CA, USAHybrid

About the Job

Requirements

  • 15+ years in network engineering and architecture, including at least 5 years as the design authority for large-scale production networks at a cloud provider, hyperscaler, content delivery network, high-performance computing or artificial intelligence infrastructure company, or carrier.
  • Hands-on experience designing, configuring, and troubleshooting networks, and building data center, backbone, and cloud networks from the ground up.
  • Current expertise in spine-leaf Clos fabrics, EVPN/VXLAN, BGP at scale, 400G/800G Ethernet, RoCEv2 and lossless Ethernet (PFC, ECN, DCQCN), and InfiniBand for GPU clusters.
  • Backbone and edge experience with multi-region interconnect, transit and peering, anycast, traffic engineering, and DDoS mitigation, with a track record of measurably reducing customer-facing latency.
  • Cloud and hybrid networking across at least two hyperscalers plus bare-metal or colocation environments, including VPC design, private interconnect (Direct Connect, ExpressRoute, Cloud Interconnect or equivalent), and VPN at scale.
  • Experience designing and operating network operations, including observability, change management, incident response, and on-call practices.
  • Proven capacity planning, including forecasting models translating product growth into bandwidth, port, and interconnect plans, and experience running the resulting procurement cycles.
  • Working experience with network automation, including Python or Go, infrastructure as code for network configuration, CI-style validation, and streaming telemetry.
  • Ability to use AI tooling in network design, configuration and automation code, telemetry analysis, and documentation to accelerate output.
  • Experience leading high-performance engineering teams, including hiring and setting standards, and ability to lead through influence without direct reports.
  • Strong ownership and comfort working in a fast-moving, ambiguous environment, identifying problems, creating clarity, and driving work to completion.
  • Based in or able to maintain full working overlap with US Pacific time.

Responsibilities

  • Own the end-to-end network architecture and define the target architecture and multi-year roadmap for the data center fabric, backbone and edge, and cloud and hybrid connectivity; make design decisions balancing latency, throughput, cost, and resilience.
  • Architect spine-leaf fabrics for multi-node inference and training, including 400G/800G Ethernet, RoCEv2 and InfiniBand, lossless transport, congestion control, and topology choices that prevent east-west traffic bottlenecks.
  • Own backbone and edge delivery, including multi-region interconnect, transit and peering strategy, anycast and traffic steering, DDoS and edge security posture, and low-latency customer response paths.
  • Design VPC, VPN, and private interconnect across hyperscalers, bare-metal providers, and colocation sites so capacity can be brought online quickly and operated consistently.
  • Define network monitoring, change, and repair practices, including telemetry and observability, change management, incident runbooks, and on-call practices; establish capabilities that do not yet exist.
  • Build capacity-planning models forecasting bandwidth, port, and interconnect needs from product growth, and turn them into procurement and build plans with appropriate lead times.
  • Automate network configuration through infrastructure as code, intent-based provisioning, automated validation and rollback, and telemetry-driven remediation.
  • Use AI tools for design exploration, configuration generation, log and telemetry analysis, documentation, and automation code, and set standards for their use across the infrastructure team.
  • Set network standards, review designs across Infrastructure, Platform, and ML Engineering, mentor engineers, and define the hiring plan and operating model for network engineering as the footprint grows.
  • Evaluate and select hardware, optics, carriers, and interconnect partners, and negotiate for performance and cost.

Desired Qualifications

  • Experience networking large GPU clusters for AI inference or training, including NVIDIA Spectrum-X, Quantum InfiniBand, NCCL tuning, or GPUDirect RDMA, and production-data-backed views on Ethernet versus InfiniBand.
  • Hands-on experience with modern network operating systems and disaggregated hardware, including SONiC, Cumulus, Arista EOS, Junos, or NVIDIA Cumulus/Spectrum platforms.
  • Experience with Ultra Ethernet, 800G and 1.6T optics, co-packaged optics, or other emerging fabric technologies.
  • Experience running peering and transit for a latency-sensitive product, including ASN management, route optimisation, and IXP presence.
  • Experience with eBPF, DPDK, SmartNICs/DPUs, or kernel-bypass networking on the host side.
  • Prior work at a startup or scale-up building the network function from zero.
  • Public contributions such as RFCs, open-source network tooling, conference talks, or published post-mortems.

About the Company

Runware

Generative AI platform with fast inference

Runware.ai provides a fast, cost-effective platform to deploy AI-generated content through an API that hides infrastructure complexity. It runs AI workloads on custom hardware in renewable-energy data centers using the Sonic Inference Engine, with real-time WebSocket connections for low-latency, scalable performance. It differentiates itself with a proprietary engine, dedicated hardware, built-in redundancy, autoscaling, GPU allocation, and access to over 188,000 models, enabling seamless integration without ML expertise. Its goal is to democratize access to generative AI for businesses by making it easy to add AI capabilities without heavy hardware costs or specialized know-how.

Company size
51-200
Company stage
Series A
Total funding
$66M
Headquarters
London, United Kingdom
Founded
2023

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