Senior Principal AI Infrastructure Architect

Salary: £41,000 - 81,000 per year

Requirements:

• Deep hands-on knowledge of AI hardware, including GPU and accelerator portfolios, host CPU platforms, system topologies, and how platform choices map to AI workloads.
• Strong understanding of AI-class storage, including parallel filesystems, all-flash NVMe platforms, object stores, checkpoint and dataset pipelines, and training and inference I/O patterns.
• Solid command of AI networking, including InfiniBand, RoCEv2, Spectrum-X, Ultra Ethernet, NVLink/NVSwitch fabrics, congestion control, and network topologies.
• Working knowledge of AI software and orchestration technologies, including CUDA, cuDNN, NCCL, ROCm, Triton, NIM, vLLM, TensorRT-LLM, Slurm, Kubernetes, Kubeflow, Run:ai, MLflow, and NVIDIA AI Enterprise.
• Familiarity with datacenter facilities engineering for AI workloads, including high-density power, liquid cooling, PUE/WUE optimization, and colocation retrofit constraints.
• Excellent written and verbal communication skills, including the ability to explain complex technical concepts to technical and executive audiences.
• Strong systems-thinking and strategic-thinking skills, with the ability to simplify complex systems to support good decisions.
• Strong business and financial skills, including cost-benefit analysis, CAPEX-versus-OPEX comparisons, and budget management.
• Knowledge of cloud, hybrid, and sovereign AI deployment patterns, as well as architectural governance for Agile, DevSecOps, and MLOps.
• Significant knowledge of managed-service portfolio artifacts, techniques, demonstrations, tools, and deliverables as applied to AI platform operations.
• Bachelors degree or equivalent in information technology, engineering, computer science, or a related field; a masters degree or PhD is advantageous.
• AI infrastructure vendor and technology certifications are highly desirable; relevant storage and networking certifications are also valued. Scaled Agile certification is advantageous.
• Significant experience in consulting, presales, or architecture within a large-scale technology services environment, preferably multinational, including a track record of leading AI infrastructure pursuits.
• Demonstrable experience designing and delivering production AI platforms, from multi-GPU servers to multi-rack training clusters and inference factories.
• Strong working knowledge of the AI hardware vendor landscape and the ability to position partner ecosystems competitively.
• Proven ability to translate AI workload requirements into accurate hardware bills of materials and sizing justifications.
• Significant client engagement and consulting experience, including needs assessment, change management, and identifying opportunities for follow-on AI infrastructure and managed-services work.
• Significant business development and presales experience on infrastructure-led deals, ideally involving sovereign AI, AI Factories, or regulated-industry generative AI programs.
• Strong understanding of how AI infrastructure integrates with business processes, applications, data platforms, and existing enterprise architecture.

Responsibilities:

• Lead end-to-end design of complex AI infrastructure solutions for enterprise, sovereign AI, and AI Factory clients, covering accelerated compute, host CPU platforms, storage, and AI networking.
• Architect reference designs using leading AI infrastructure platforms, balancing single-node performance with cluster-scale efficiency.
• Size and validate GPU clusters for pre-training, fine-tuning, retrieval-augmented generation, and real-time and batch inference workloads.
• Define supporting datacenter designs, including high-density power, liquid cooling, AI-fabric cabling, and modular deployment models across on-premises, colocation, and sovereign-cloud environments.
• Work with our sales team to lead presales activities, including client discovery, technical workshops, proposal writing, executive presentations, and bid defense.
• Translate clients AI ambitions and business outcomes into hardware and platform roadmaps, positioning our end-to-end portfolio to deliver service-led AI solutions.
• Lead integration of compute, storage, networking, AI software, and managed-service operating models across domains, delivery units, and geographies.
• Build business cases, total-cost-of-ownership and unit-economics models, and transition roadmaps for cloud-to-private AI migrations and sovereign AI deployments.
• Define and apply architectural principles for AI infrastructure, including accelerator utilization, data gravity, multi-tenancy, model lifecycle, and energy efficiency.
• Develop current-state, vision, future-mode-of-operation, and target AI platform architectures; identify gaps and develop transition roadmaps.
• Synthesize trends in AI silicon, memory hierarchies, interconnects, and AI software with clients strategic priorities to create evidence-based solutions.
• Contribute reference architectures, sizing tools, and lessons learned to our AI Factories knowledge base for internal teams and clients.

Technologies:

• AI
• Architect
• Cloud
• CUDA
• DevSecOps
• Ethernet
• Fabric
• Fine-tuning
• Hardware
• InfiniBand
• Support
• Kubeflow
• Kubernetes
• LLM
• Liquid
• MLflow
• MLOps
• Network
• Security
• vLLM
• NodeJS
• Cisco
• DDN
• Nexus
• Nutanix
• OpenShift
• RAG

More:

We are NTT DATA, a global business and technology services leader serving 75% of the Fortune Global 100. We work to accelerate client success and positively impact society through responsible innovation, with capabilities across enterprise-scale AI, cloud, security, connectivity, data centers, and application services. As part of NTT Group, which invests more than $3 billion annually in R&D, we offer access to innovation centers and a broad ecosystem of established and startup partners. We are a Global Top Employer with experts in more than 50 countries, and our inclusive workplace supports employees growth and development. This is a full-time Senior Principal AI Infrastructure Architect role at the center of our AI Factories practice, focused on the hardware foundations for enterprise-scale AI. The role is remote, with locations listed in Segrate, Italy; Belgium; France; the United Kingdom; and Luxembourg.

last updated 40 week of 2026