End to End Architect

About WWT

World 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.

• 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 stakeholders

• 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 performance

• 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 deployments

• 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, Infini Band 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

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