Join our dynamic Technology & Transformation practice and help shape the future of data and AI. You will leverage your expertise to guide companies in managing vast datasets and converting them into actionable insights, driving data-driven decision-making.

This role is pivotal in managing complex data landscapes and implementing cutting-edge solutions in business intelligence, data management, and advanced analytics. You'll work with emerging technologies like big data, cloud, cognitive computing, and machine learning.

Translate AI workload demands into detailed infrastructure requirements, including GPU, compute, network, storage, power, and cooling. Develop AI infrastructure strategies and roadmaps, defining target architectures and capacity plans for hybrid environments.

Build compelling business cases for hybrid cloud solutions, encompassing GPU economics, facilities, networking, storage, software, and operational costs. Lead AI data-centre readiness assessments, ensuring alignment with density, power, cooling, and resilience standards.

A seasoned professional with over 15 years of experience in infrastructure, platform engineering, HPC, cloud, or AI infrastructure. Expertise in NVIDIA GPU architecture and production AI/GPU platforms is essential.

Demonstrated experience in GPU cluster architecture, high-performance networking, storage, and AI data-centre infrastructure is crucial. Strong understanding of distributed AI workloads, GPU scheduling, Kubernetes/OpenShift, and/or Slurm is required.

Proven ability to develop capacity models, TCO/ROI cases, and executive decision papers. Excellent client-facing leadership, stakeholder management, and commercial estimation skills are necessary.