Principal AI Network Engineer

About Highrise AI Highrise AI is a GPU-native infrastructure platform built for modern AI workloads. Designed for developers and enterprises operating in performance-critical and security-sensitive environments, Highrise delivers scalable GPU compute across dedicated clusters, managed cloud, and confidential environments. Highrise combines bare-metal performance with full-stack orchestration, API-driven access, and hardware-enforced isolation to support training, fine-tuning, and production-scale deployment of AI models. From reserved GPU capacity to enterprise-grade confidential compute, Highrise provides flexible infrastructure models tailored to the needs of builders operating at scale. Beyond infrastructure, Highrise integrates disciplined operations, advanced automation, and on-site engineering expertise to sustain high uptime and predictable performance across deployments. These capabilities extend beyond Highrise-owned fleets: through managed services, Highrise also operates third-party GPU hardware on behalf of customers and partners, applying the same operational standards to infrastructure it does not own. Highrise is a subsidiary of Hut 8 Corp., an energy infrastructure platform. Hut 8 integrates power, digital infrastructure, and compute at scale. Highrise serves as the compute and operations layer—designing, deploying, and operating next-generation GPU clusters from commissioning through production. ROLE OVERVIEW We are seeking a principal-level, hands-on AI Network Engineer to bring large-scale GPU cluster networks from physical installation and cabling to fully configured, validated, and commercially ready operation. Working alongside senior compute, storage, and infrastructure engineers, this person will lead network fabric bring-up, advanced configuration, performance tuning, and technical acceptance across AI training and supporting infrastructure networks. Following deployment, the engineer will serve as a Tier 3 escalation point for complex production networking issues, driving root cause analysis, reliability improvements, and ongoing optimization of high-performance AI clusters. KEY RESPONSIBILITIES Network Fabric Bring-Up and Integration • Lead network commissioning of materially complete AI clusters, including switch initialization, configuration validation, host connectivity, and readiness for production workloads. • Configure and integrate high-speed Ethernet and/or InfiniBand compute fabrics, including RDMA/RoCE, alongside storage, management, and out-of-band networks. • Validate topology, routing, redundancy, addressing, port mappings, optics, cabling, and interoperability across switches, NICs, and supporting systems. • Implement and refine network automation, configuration management, firmware/OS baselines, and repeatable fabric deployment procedures. • Partner with compute and storage engineers to resolve host-to-fabric integration issues and ensure end-to-end cluster readiness. Performance Optimization and Acceptance • Execute fabric qualification and acceptance testing for link health, error rates, bandwidth, latency, congestion, resilience, and scaling behavior. • Troubleshoot and tune RDMA transport, congestion control, QoS, PFC/ECN, routing, and switch/NIC settings as appropriate to the deployed fabric. • Analyze NCCL and distributed workload results with compute engineers to isolate communication bottlenecks and improve multi-node performance. • Use telemetry, switch counters, fabric management platforms, and diagnostic tools to identify degraded links, optical issues, packet loss, or unexpected congestion. • Own networking acceptance evidence, defect remediation, configuration sign-off, and readiness recommendations for commercial service. Tier 3 Operations and Network Rel