Lead the architectural vision and execution for cutting-edge AI infrastructure. This Director role focuses on designing and deploying robust, scalable, and high-performance GPU compute environments.

You will be instrumental in shaping the future of AI capabilities by defining end-to-end solutions, from hardware to software, ensuring optimal performance, efficiency, and reliability for complex AI workloads.

This is an opportunity to drive innovation, build a world-class engineering team, and make a significant impact on the strategic direction of AI infrastructure services.

Oversee the complete architecture of NVIDIA GPU compute, CPUs, DPUs, and associated infrastructure including networks, storage, and security. Design and implement state-of-the-art DGX/HGX GPU clusters optimized for various AI tasks like training, fine-tuning, and inference.

Architect high-performance networking solutions with InfiniBand and Ethernet, and define advanced file and object storage strategies. Engineer AI data center requirements, including power, cooling, and physical layout. Implement and manage Kubernetes/OpenShift or Slurm platforms with a focus on GPU scheduling and workload isolation.

Integrate and operationalize NVIDIA AI Enterprise suite and related services. Establish automated processes for provisioning, firmware management, and performance testing. Operate the platform using SRE principles, ensuring observability, incident management, and robust security controls. Optimize GPU utilization, job throughput, and cost-effectiveness. Drive the market proposition, account strategy, and foster strategic alliances for AI infrastructure services.

Shape multi-year AI transformation programs, lead commercial negotiations, and manage delivery quality and risk. Build, mentor, and retain a high-performing team of AI infrastructure specialists.

A minimum of 18 years of experience in infrastructure, cloud, data center, HPC, or platform engineering is essential, with significant leadership in production AI/GPU environments. Proven experience in business development, executive advisory, strategic alliances, and governing large-scale technology programs is required.

Demonstrate strong expertise in NVIDIA GPU architectures and systems, and proven experience designing GPU clusters encompassing compute, networking, storage, and control planes. Possess a deep understanding of AI workload characteristics and hands-on architecture and leadership experience with Kubernetes/OpenShift and/or Slurm. Proficiency in Linux, containerization, CUDA ecosystem, NCCL, GPU drivers, firmware, and observability fundamentals is crucial.

Require proven experience with production AI infrastructure, including security, resilience, capacity management, performance optimization, automation, and day-2 operations. Strong understanding of high-density data center environments and experience designing/operating high-performance storage and InfiniBand/Ethernet fabrics are necessary. Excellent commercial acumen, stakeholder management, and executive communication skills are vital.