Senior Principal Ai Infrastructure Architect
Pubblicato il 01-10-2026 - Ntt Data in Cuneo
In this role you will lead the design of enterprise-grade AI infrastructure, shaping how clients train, fine-tune and deploy AI at scale. You will sit at the core of NTT DATA's AI Factories practice, aligning hardware, software, and managed services with client outcomes. You’ll drive architectural decisions, coordinate with cross-functional teams, and guide complex, multi-site deployments. This is a机会 to influence large-scale AI platforms and advance responsible, scalable AI solutions.
- Diversity and inclusion
- Global exposure and collaboration
- Work with cutting-edge AI infrastructure
- Competitive benefits (as per company)
- Lead end-to-end design of large, complex AI infrastructure solutions for enterprise and sovereign AI clients
- Architect reference designs on NVIDIA DGX/HGX, Dell AI Factory, Cisco HyperFabric AI and other accelerated compute platforms
- Size and validate GPU clusters and storage for foundation-model training, fine-tuning, RAG, inference
- Define datacenter design for high-density power, cooling, and cabling across on-prem, colo and sovereign cloud
- Collaborate with sales to drive presales activities and client workshops
- Translate AI ambitions into a hardware/platform roadmap across silicon, systems, storage, fabric, and MLOps
- Lead integration of compute, storage, networking, AI software stack, and managed-service models across domains
- Build business cases, TCO and transition roadmaps for cloud-to-private AI migrations and sovereign deployments
- Define architectural principles for AI infrastructure and governance
- Develop As-Is, Vision, FMO and To-Be AI platform architectures and transition roadmaps
- Synthesize AI silicon trends with client imperatives to craft compelling, evidence-based solutions
- Contribute to AI Factories knowledge base with reference architectures and sizing tools
- Significant experience in a consulting/presales/architecture role in a large-scale technology services environment
- Proven track record designing and delivering production AI platforms from single multi-GPU servers to multi-rack training clusters
- Strong working knowledge of AI hardware vendors and partner ecosystems
- Ability to translate AI workload requirements into hardware BOMs and sizing justifications
- Extensive client engagement, needs assessment, and change management experience
- Business development and presales experience on infrastructure-led deals, including sovereign AI or GenAI programs
- Understanding of AI infrastructure integration with business processes, apps, and data platforms
- Knowledge of cloud, hybrid and sovereign AI deployment patterns and governance for Agile/DevSecOps/MLOps xjncmbx
- Familiarity with managed service artefacts and deliverables for AI platform operations
- Bachelor in Information Technology / Engineering / Computer Science; Master/PhD advantageous
- Vendor certifications in AI infrastructure desirable (e.g., NVIDIA, Dell, Cisco, HPE, Run:ai)
- Scaled Agile certification advantageous
- Significant multinational consulting experience and ability to work across geographies
- Strong communication and strategic-thinking skills
- Proven ability to build CAPEX vs OPEX models and budgets
- excellent written and oral communication
- strong systems-thinking
- strategic-thinking
- AI hardware: NVIDIA Hopper/Blackwell, AMD MI300/MI325, Intel Gaudi 3; CPU platforms: Intel Xeon, AMD EPYC, NVIDIA Grace
- Networking: InfiniBand NDR/XDR, RoCEv2, NVIDIA Spectrum-X, NVLink/NVSwitch
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