Senior Director, HPC Deployment at Scale

About this role

Job Type: Full-Time | Location: Remote | Department: Network | Reporting to: Vice President, Cloud | Work Location Type: #remote #hybrid

IREN is a vertically integrated AI Cloud provider, delivering large-scale data centers and GPU clusters for AI training and inference. IREN’s platform is underpinned by its expansive portfolio of grid-connected land and power in renewable-rich regions across North America, Europe and APAC.

With 100% renewable energy, we build, own and operate our data centers and take pride in being at the forefront of sustainable solutions for the ever-evolving applications of high-performance compute. We believe that human progress is invaluable, but it should be done in the right way – responsibly, sustainably and having a positive impact on the communities we operate in.

TheSenior Director of HPC Deploymentat Scale will lead the organization responsible for high-volume deployment of GPU and high-performance computing clusters across data centers. This leader takes validated engineering packages, golden builds, deployment procedures, automation, and QA/QC standards from the HPC New Product Introduction (NPI) / FOAK organization and turns them into a repeatable production deployment capability.

This is an execution-at-scale leadership role. The organization will deploy many clusters concurrently across the complete infrastructure stack, including GPU and CPU compute, InfiniBand and Ethernet/RoCE networking, storage integration, management infrastructure, provisioning, automation, observability, and operational tooling.

Delivering production GPU capacity on time and with exceptional quality is fundamental to success. The Senior Director will build the operating system, leadership structure, processes, automation, quality controls, and metrics required to repeatedly deliver against aggressive capacity commitments across many sites and deployments.roduction readiness.Responsibilities

• Own end-to-end execution of large-scale GPU/HPC cluster deployments from deployment readiness through physical installation, network and compute bring-up, provisioning, QA/QC, cluster integration, validation, burn-in, production acceptance, and operational handoff. Build an organization capable of executing many deployments simultaneously while maintaining consistent engineering and quality standards.

• Consume approved engineering packages from the NPI/FOAK organization and execute them with discipline. Ensure every deployment follows the approved reference architecture, bill of materials, topology, rack and cabling standards, network configuration, firmware and software versions, provisioning workflows, QA/QC requirements, validation procedures, and production acceptance criteria. Prevent uncontrolled design deviations and use formal engineering escalation and change-control mechanisms when changes are required.

• Own delivery against committed GPU capacity dates. Establish detailed deployment plans, milestones, critical paths, dependencies, site-readiness criteria, and delivery forecasts. Maintain clear visibility into the status and confidence level of every deployment. Identify risks early and drive mitigation and recovery plans across data center, supply chain, networking, compute, storage, software, vendors, and operations.

• Own QA/QC throughout the scaled deployment lifecycle. Ensure quality gates are consistently executed across hardware installation, rack configuration, cabling and optics, InfiniBand and RoCE fabrics, GPU and compute health, firmware and BIOS, operating systems and drivers, storage connectivity, management infrastructure, provisioning, observability, performance, and reliability. Track first-pass yield, defects, rework, quality escapes, and production acceptance across deployments and sites.

• Build a deployment factory that treats cluster deployment as an engineered production system. Standardize workflows, staffing models, tooling, sequencing, quality gates, escalation paths, and deployment practices across locations. Continuously improve throughput, cycle time, first-pass quality, predictability, automation, and repeatability while reducing site-to-site variance and configuration drift.

• Drive an automation-first deployment model. Partner with NPI and engineering organizations to automate readiness checks, hardware discovery, network configuration, firmware and BIOS validation, bare-metal provisioning, cluster configuration, topology and connectivity validation, GPU health checks, performance testing, QA/QC, burn-in, and production acceptance. Convert repeatable manual procedures into software wherever practical.

• Create a strong feedback loop from scaled deployment into NPI and engineering. Capture recurring defects, documentation gaps, automation gaps, hardware-quality issues, configuration problems, vendor issues, performance anomalies, and deployment bottlenecks. Use structured data from many deployments to improve future golden builds and ensure changes are incorporated through disciplined version control.

• Ensure clusters are not considered delivered simply because installation is complete. Production delivery requires successful completion of defined engineering, quality, performance, reliability, and operational acceptance criteria. Partner with SRE and operations teams to ensure the infrastructure being handed over is stable, observable, supportable, and ready for production workloads.

• Build and lead a large multidisciplinary organization spanning HPC/GPU deployment, network deployment, cluster integration, systems engineering, infrastructure automation, QA/QC, validation engineering, site leadership, and technical program management. Develop leaders capable of managing multiple large deployments concurrently and create a culture centered on execution, urgency, accountability, standardization, quality, and continuous improvement.

Requirements

• 15+ years of experience in infrastructure, HPC, cloud, networking, data center, or…