End to End Architect
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Key skills for this role
About the Role
World Wide Technology is seeking an End-to-End AI Infrastructure Architect to design and integrate compute, networking, storage, facilities, and platform layers into coherent AI infrastructure architectures.
Key Skills for This Role
Responsibilities
- 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
Requirements
- 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
Full Job Posting
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’s AI Infrastructure Practice designs, deploys, and operates the physical and logical foundations that make enterprise AI possible.
The Opportunity
- Most AI infrastructure failures happen at the seams — where compute meets network, where storage meets platform, where facilities meet hardware.
- As an End to End AI Infrastructure Architect, you bring together compute, networking, storage, facilities, platform, and security into coherent architectures.
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 stakeholders.
Must 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 performance.
Nice 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 deployments.
Why 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.
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