AI Infrastructure Delivery Lead
Location: London (with expected travel)
Salary: Competitive, plus benefits.
In this role you will:
Accenture’s Infrastructure Architecture & Engineering practice, within our Digital Core Reinvention group, is focused on providing best in class hybrid cloud infrastructure for large enterprise clients. Our team provides full lifecycle cloud and infrastructure services from consulting on strategy to leading large technology implementations.
Accenture’s Infrastructure Delivery Leads, manage high performing teams across consulting, delivery management, project execution, and technical expertise to partner with our clients to plan, analyse, design, test, and deploy enterprise scale end-to-end hybrid cloud transformation solutions.
Responsibilities:
Design, architect and lead the delivery of AI-ready infrastructure platforms that enable large-scale machine learning (ML), generative AI (GenAI), agentic AI and high-performance computing (HPC) workloads.
The successful candidate will be responsible for defining AI compute architectures across on-premises, colocation and cloud environments, helping clients establish secure, scalable and cost-efficient GPU platforms that support training, fine-tuning and inference workloads.
Job Qualifications
Strong client-facing consulting experience.
Ability to engage effectively with CIO, CTO and AI leadership teams.
Excellent written and verbal communication skills.
Experience leading distributed architecture and engineering teams.
Commercial awareness and business case development capability.
Infrastructure design, build, and management experience in some of the following areas:
Infrastructure fundamentals (e.g., Datacenter, Networks, Compute, Storage)
Cloud and Infrastructure Migrations, Operations and Lifecycle management
Cloud services (e.g., Amazon Web Services, Microsoft Azure, Google Cloud Platform)
Cloud and Infrastructure Security & Resilience (DR, HA, Backup & Recovery)
Virtualization Platforms (e.g., VMware, Hyper-V, Nutanix)
Container Platforms (e.g., Openshift, EKS, AKS, GKS)
Infrastructure Automation (e.g., Terraform, Ansible, Python)Demonstrable experience with:
GPU-based infrastructure design
NVIDIA AI ecosystem
CUDA and GPU architectures
AI training environments
AI inference platforms
HPC infrastructure
AI workload scheduling
ML platform architectures
