Enterprise Architect - AI

World Wide Technology is looking for a deeply technical Enterprise Architect who will own the delivery of AI projects end to end from the silicon and data centre design that underpins AI workloads, through the software and MLOps stack, to the governance frameworks that make AI trustworthy and defensible at scale. This is a technical hardware-and-software architect role, not a strategy-only position. The successful candidate operates comfortably across GPU infrastructure, high-performance networking, model training and inference pipelines, and the AI risk/governance disciplines increasingly demanded by regulators and enterprise boards.

The Enterprise Architect will lead technical delivery teams for client engagements, acting as the single point of technical accountability from design through to go-live, while mentoring delivery teams and shaping WWT’s broader AI point of view.

• Own end-to-end technical delivery of AI/ML engagements: architecture definition, design authority, build oversight, and go-live validation.
• Host and chair Architecture Review Board (ARB) and Technical Design Authority (TDA) sessions, owning governance gates, decision records, and design sign-off.
• Architect AI infrastructure spanning GPU/accelerator compute, high-performance interconnects, parallel/high-throughput storage, and orchestration.
• Design the AI software stack: training and fine-tuning pipelines, distributed training frameworks, inference/serving platforms, MLOps/LLMOps tooling, vector databases, retrieval-augmented generation (RAG) and agentic architectures.
• Define AI governance frameworks covering model risk management, responsible AI, data lineage, bias/fairness testing, explainability, and regulatory alignment (EU AI Act, NIST AI RMF, ISO/IEC 42001).
• Act as trusted technical advisor to client CTOs, CIOs, and Heads of Data/AI on platform strategy, build-vs-buy decisions, and AI operating model design.
• Lead technical workshops, architecture design sessions, and proof-of-concept builds with cross-functional teams.
• Serve as the technical escalation point for delivery teams; unblock design and implementation issues under time pressure.
• Mentor other architects and engineers on AI systems design.
• Partner with sales and pre-sales to scope AI solutions, size infrastructure, and validate technical feasibility of proposed architectures.
• Define automation, orchestration, and observability standards across the AI stack.
• Architect integration points connecting AI platforms to existing enterprise networks, third-party systems, and external or service-provider-hosted environments.

• GitOps (ArgoCD) for continuous, declarative platform delivery.
• Pipeline orchestration: Kubeflow Pipelines, Apache Airflow, or Argo Workflows.
• Cluster final technical authority on an engagement.
• Mentors junior and mid-level architects, raising the technical bar.
• Builds credibility with highly technical client stakeholders and executive sponsors.
• Thrives on ambiguity in a fast-moving technology space.
• Collaborates effectively across sales, pre-sales, delivery, and partner teams.

• Ability to author low-level and high-level design documentation.
• Strong verbal and written communication with senior clients and multi-vendor delivery teams.

• Networking and data centre design (routing/switching, fabric architectures).
• Storage architecture (all-flash arrays, software-defined storage, parallel file systems).
• Cybersecurity architecture, particularly zero trust and data protection.
• Traditional enterprise application and integration architecture.
• Software development background (Python, Go, or similar) for tooling and automation.
• Virtualization/private cloud platforms (VMware, OpenShift/OpenStack).

• NVIDIA certifications (NCP-AI Infrastructure, NVIDIA Deep Learning Institute credentials).
• Cloud AI/ML certification: AWS Certified Machine Learning – Specialty, Microsoft Certified: Azure AI Engineer Associate, or Google Professional Machine Learning Engineer (at least one).
• Kubernetes: CKA or CKAD.
• TOGAF 9/10 or equivalent enterprise architecture certification.

• Bachelor’s degree in Computer Science, Computer Engineering, or a related technical field, or equivalent demonstrable experience.
• Advanced degree (MS in CS/AI/ML or related) beneficial but not required.

WWT will consider for employment, without regard to disability, a disabled applicant who satisfies the requisite skill, experience, education, and other job-related requirements of the job and is capable of performing the essential requirements of the job with or without reasonable accommodation. World Wide Technology is an Equal Opportunity Employer. Employment decisions are made without regard to race, colour, religion, sex (including pregnancy), sexual orientation, gender identity, national origin, age, disability, veteran status, genetic information, or other characteristics protected by law. We are committed to working with and providing reasonable accommodations to individuals with disabilities.