End to End Architect

About WWTWorld Wide Technology (WWT) is a global technology solutions provider with over US$20 billion in annual revenue, 10,000+ employees, and operations across the Americas, EMEA, and APAC. WWT combines strategy, execution, and partnership to help the world’s largest organisations adopt transformative technology — from cloud and security to AI and advanced infrastructure.WWT’s AI Infrastructure Practice designs, deploys, and operates the physical and logical foundations that make enterprise AI possible — GPU compute clusters, high-performance networking, storage architectures, power and cooling systems, and the platforms that tie them together. As eleven-time NVIDIA Partner of the Year for AI and Deep Learning, WWT brings unmatched depth in AI infrastructure at enterprise scale.The OpportunityMost AI infrastructure failures happen at the seams — where compute meets network, where storage meets platform, where facilities meet hardware. You will be the integrator who prevents this.As an End-to-End AI Infrastructure Architect, you bring together compute, networking, storage, facilities, platform, and security into coherent architectures that actually work when thousands of GPUs need to train a model together. You will be the named Design Authority on WWT’s most complex AI infrastructure programmes, ensuring every component works as a system.What You’ll Do Integrate compute, networking, storage, facilities, and platform layers into unified AI infrastructure architectures Serve as named Design Authority on major AI infrastructure programmes — owning the architectural integrity end-to-end Map AI infrastructure architectures to client business outcomes: cost-per-training-run, time-to-inference, utilisation efficiency Evaluate and recommend vendor-neutral component stacks: GPU compute (NVIDIA, AMD), networking, storage, and platform Design reference architectures for common AI infrastructure patterns: training clusters, inference farms, hybrid training/inference Coordinate between domain specialists (networking, storage, MEP, platform) to resolve cross-domain design conflicts Conduct architectural reviews and risk assessments at programme milestones Present architecture decisions and trade-offs to client CTO/VP-level stakeholdersWhat We’re Looking ForMust-Haves 15+ years in infrastructure and solution architecture, spanning compute, networking, and storage 3-5+ years designing AI/ML or HPC infrastructure platforms at scale TOGAF, SABSA, or equivalent architecture framework experience Vendor-neutral evaluation capability across GPU compute, networking, storage, and platform vendors Client-facing design authority experience on programmes of significant scale Systems-level thinking — ability to understand how component interactions affect overall system performanceNice-to-Haves Experience with NVIDIA DGX/HGX SuperPOD reference architectures Understanding of AI platform software: Kubernetes, Slurm, Base Command Manager Knowledge of TCO modelling for AI infrastructure (build vs colo vs cloud) Experience with air-gapped or sovereign AI infrastructure deploymentsWhy WWT Join a US$20B+ global technology leader with startup energy in the AI Infrastructure practice Work on the most advanced AI infrastructure deployments in EMEA — GPU superclusters, liquid cooling, InfiniBand fabrics Direct access to NVIDIA, HPE, Dell, Cisco, and leading AI infrastructure vendors as strategic partners Enterprise-scale projects with Fortune 500 and regulated industry clients Remote-first flexibility with travel to client sites and data centres Competitive compensation, benefits, and professional development,NA