End-to-End AI Infrastructure Architect

About the role

World Wide Technology (WWT) is seeking an End‑to‑End AI Infrastructure Architect to lead the design of large‑scale AI compute environments. The role bridges compute, networking, storage, facilities and platform layers to deliver coherent architectures that support thousands of GPUs for model training and inference.

Key responsibilities

• Integrate compute, networking, storage, facilities and platform components into unified AI infrastructure architectures.
• Act as the named Design Authority on major AI infrastructure programmes, ensuring architectural integrity from concept to delivery.
• Map AI infrastructure designs to client business outcomes such as cost‑per‑training‑run, time‑to‑inference and utilisation efficiency.
• Evaluate and recommend vendor‑neutral component stacks, including GPU compute (NVIDIA, AMD), networking, storage and platform solutions.
• Design reference architectures for common AI patterns like training clusters, inference farms and hybrid environments.
• Coordinate with domain specialists to resolve cross‑domain design conflicts and conduct architectural reviews and risk assessments.
• Present architecture decisions and trade‑offs to senior client stakeholders (CTO/VP level).

Required profile

• 15+ years of experience in infrastructure and solution architecture covering compute, networking and storage.
• 3‑5+ years designing AI/ML or HPC infrastructure platforms at enterprise scale.
• Proficiency with an architecture framework such as TOGAF or SABSA.
• Demonstrated client‑facing design authority on large‑scale programmes.
• Systems‑level thinking with the ability to assess component interactions on overall performance.

Required skills

• NVIDIA and AMD GPU compute technologies.
• Kubernetes.
• Slurm workload manager.
• Base Command Manager.
• TOGAF.
• SABSA.