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IREN

Operates renewable-powered AI GPU cloud infrastructure

Senior Director of HPC Delivery

Engineering LeadershipConfirmed live in the last 24 hours
Full-timeTexas, USA

About the Job

Requirements

  • At least 15 years of experience in infrastructure, high-performance computing, cloud, data center, networking, or large-scale distributed systems, including at least 8 years leading highly technical engineering organizations.
  • Demonstrated experience delivering complex, large-scale infrastructure programs against aggressive schedules and demanding quality requirements.
  • Strong understanding of GPU-based computing architectures and high-performance networking, particularly InfiniBand and/or Ethernet/RoCE.
  • Broad technical knowledge across compute, networking, storage, Linux, firmware, drivers, provisioning, infrastructure automation, and management systems.
  • Experience establishing quality assurance and quality control, validation, commissioning, burn-in, and production acceptance processes for complex infrastructure.
  • Demonstrated ability to lead cross-functional programs and solve system-level issues spanning hardware and software domains.

Responsibilities

  • Lead end-to-end delivery of first-of-kind GPU/high-performance computing clusters from architecture handoff through installation, commissioning, integration, validation, burn-in, production acceptance, and handoff to scaled deployment. Own execution across the complete cluster stack and resolve complex issues spanning hardware, firmware, GPU, CPU, networking, storage, operating systems, drivers, provisioning, and management tooling.
  • Establish a rigorous quality assurance and quality control framework throughout the delivery lifecycle, including measurable quality gates and acceptance criteria for physical installation, cabling and optics, InfiniBand and RoCE fabrics, compute and GPU health, firmware and BIOS, operating systems and drivers, storage connectivity, management systems, configuration compliance, automation, observability, performance, and reliability.
  • Establish program milestones, critical paths, dependencies, readiness criteria, and executive reporting for each first-of-kind program. Identify technical, site, supply-chain, vendor, schedule, and quality risks early, assign ownership, and drive mitigation or recovery plans before committed capacity dates are affected.
  • Partner with architecture and engineering teams to translate new designs into deployable systems. Provide rapid feedback when designs encounter real-world integration, manufacturing, quality, reliability, or operational constraints, and drive design-for-deployability, design-for-quality, and design-for-operability.
  • Convert successful first-of-kind deployments into a complete golden build and deployment package, including reference architecture, bills of materials, physical and logical topology, rack and cabling standards, network configurations, firmware and software compatibility, provisioning workflows, configuration standards, quality assurance and quality control procedures, automated validation, burn-in, performance benchmarks, troubleshooting procedures, defect-remediation playbooks, and production acceptance criteria.
  • Create documentation that enables another organization to reproduce the cluster without depending on tribal knowledge, explaining how to build, inspect, validate, troubleshoot, and determine production readiness.
  • Establish a formal new-product-introduction-to-scale handoff process with measurable readiness criteria. Ensure the Deployment at Scale organization has the engineering package, automation, training, quality standards, escalation paths, and operational knowledge needed to repeat builds consistently across sites and regions. Remain engaged during early scaled deployments to resolve systemic issues and improve the golden build.
  • Drive an automation-first approach to deployment and quality. Partner with software, platform, network, and infrastructure engineering teams to automate provisioning, configuration, pre-flight checks, topology validation, hardware and firmware validation, quality assurance and quality control, performance testing, and production acceptance. Use deployment data to identify recurring defects and eliminate sources of rework.
  • Build and lead a multidisciplinary organization spanning high-performance computing and GPU infrastructure, networking, cluster integration, systems engineering, automation, quality engineering, validation, and technical program delivery.
  • Create a culture of urgency, engineering rigor, accountability, documentation, quality, and continuous improvement.

About the Company

IREN

Operates renewable-powered AI GPU cloud infrastructure

IREN runs renewable-powered AI cloud and digital infrastructure by operating data centers and GPU clusters. Customers access high-performance NVIDIA GPUs and AI training/inference infrastructure through cloud-based services powered by grid-connected and renewable energy assets. It differentiates itself through full vertical integration of energy assets with compute infrastructure and a focus on North America. The company aims to provide scalable, renewable-powered AI compute for enterprises and developers to support large-scale AI workloads.

Company size
501-1,000
Company stage
IPO
Headquarters
Sydney NSW, Australia
Founded
2018

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