Enterprise Architect – AI

Role Overview

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 center 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.

Key Responsibilities

• 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.

Infrastructure, Tools & Platforms

Infrastructure‑as‑code: Terraform and Ansible for repeatable, automated provisioning of GPU clusters and AI platform environments; GitOps (ArgoCD) for continuous, declarative platform delivery. Pipeline orchestration: Kubeflow Pipelines, Apache Airflow, or Argo Workflows. Cluster & workload scheduling: Slurm, Run:ai, NVIDIA Base Command Manager, Kubernetes‑native GPU scheduling. CI/CD/CT for ML. Infrastructure & GPU observability: NVIDIA DCGM, Prometheus/Grafana, etc. Model & LLM observability: Arize, WhyLabs, Langfuse. Logging & tracing: ELK/OpenSearch, OpenTelemetry. Integration: API‑based and event‑driven AI platform integration with enterprise systems (REST/gRPC, Kafka). Enterprise network integration: capacity and latency planning. Hybrid & multi‑cloud connectivity: Direct Connect, ExpressRoute, multi‑cloud/hybrid patterns. Secure exposure of AI services: API gateways, service mesh, mutual TLS. Cross‑functional design with network and security architects.

Governance, Risk & Compliance

Working knowledge of model risk management frameworks, responsible AI principles (fairness, explainability, human oversight), data privacy regulation (GDPR, CCPA), emerging AI‑specific regulation and standards (EU AI Act, NIST AI Risk Management Framework, ISO/IEC 42001). Experience establishing model documentation, audit trail, and approval‑gate processes for production AI systems.

Leadership & Delivery Expectations

Leads technical delivery independently with minimal oversight; 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.

Experience & Technical Qualifications

• 10+ years in enterprise architecture, infrastructure engineering, or platform engineering roles.
• 5+ years focused specifically on AI/ML systems design and delivery, including at least 2 years working with generative AI/LLM workloads.
• Demonstrated track record leading technical delivery on enterprise‑scale AI or HPC infrastructure programmes.
• Depth in AI hardware & data center infrastructure: GPU/accelerator architectures (NVIDIA / AMD), accelerator interconnects (NVLink, NVSwitch), high‑performance networking (InfiniBand, RoCEv2, 400G/800G Ethernet), data center facilities. Storage: parallel, high‑throughput file systems.
• AI software: Kubernetes, Docker, Slurm, Run:ai or equivalent scheduling platforms. ML frameworks: PyTorch, TensorFlow. Distributed training: Horovod, DeepSpeed, Megatron‑LM. Inference & serving: NVIDIA Triton, vLLM, TensorRT‑LLM. MLOps/LLMOps: Kubeflow, MLflow, SageMaker, Azure ML, Vertex AI. Generative AI: LLM fine‑tuning (LoRA/QLoRA), RAG, vector databases, agentic frameworks (LangChain, LangGraph, Semantic Kernel). Data pipelines: lakehouse architectures, ETL/ELT, data quality/lineage tooling.
• AI‑specific security fundamentals: model security, prompt‑injection defenses, supply‑chain security for open‑source/open‑weight models.
• Solution‑architect level expertise in at least one hyperscaler (AWS, Azure, or GCP) and ability to design for hybrid on‑premises/cloud deployments, including data residency and sovereignty constraints.
• Proven experience hosting and chairing formal Architecture Review Board (ARB) and Technical Design Authority (TDA) forums.
• Experience producing and maintaining architecture decision records (ADRs), design standards, and reference architectures.
• Excellent executive communication and presentation skills; ability to author low‑level and high‑level design documentation.
• Strong verbal and written communication with senior clients and multi‑vendor delivery teams.

Additional Skills (Strong Plus)

• Networking and data center 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).

Certifications

• 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.

Education

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.

EEO Statement

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, color, 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. If you have a disability and you believe you need a reasonable accommodation in order to search for a job opening or to submit an online application, please call 1‑800‑432‑7008 and ask for Human Resources.

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