Solutions Architect - Nvidia Cloud Partners and Datacentre Infrastructure

NVIDIA NVIDIA · Semiconductors · Dubai, United Arab Emirates

Solutions Architect focused on datacentre infrastructure (power, cooling, MEP) to support AI and HPC GPU deployments. Collaborates with customers and partners to design, implement, and operationalize NVIDIA's hardware and software solutions, ensuring robust and efficient datacentre environments. Provides technical guidance and feedback to business and engineering teams.

What you'd actually do

  1. Work closely with NVIDIA Cloud Partners to design, implement, and operationalise NVIDIA's cutting-edge hardware and software solutions, ensuring seamless integration with datacentre power, cooling, and MEP systems.
  2. Collaborate with Sales Account Managers and other business leads to identify and secure business opportunities for NVIDIA products and solutions, including those involving datacentre infrastructure upgrades and expansion.
  3. Serve as the primary technical contact for customers throughout the development, construction, and production of extensive GPU cloud infrastructure, providing guidance on datacentre power distribution, cooling strategies, and MEP integration across the full customer lifecycle.
  4. Conduct regular technical customer meetings to discuss project and product details, features, introduction to new technologies, debugging sessions, and address datacentre-related challenges such as optimising power usage and cooling efficiency.
  5. Work with customers to build Proofs of Concept (PoCs) for solutions that tackle critical business needs, including the development of robust networking, compute, and MEP infrastructure to meet demanding AI and HPC workloads.

Skills

Required

  • BS/MS/PhD in Mechanical/Electrical Engineering, or other Engineering fields or equivalent experience
  • 12+ years of Solution Engineering (or similar Sales Engineering, Cloud Engineering) experience working directly with partners and customers
  • Experience crafting and deploying large-scale cluster environments
  • Practical expertise in datacentre design, development, and execution for AI and HPC
  • Efficient time management and capable of balancing multiple tasks
  • Ability to communicate ideas clearly through documents, presentations, etc.

Nice to have

  • Practical familiarity with large datacentre design, power distribution, and cooling (liquid to chip)
  • Practical familiarity with NVIDIA hardware (such as GPUs, ETH/IB networking components, storage, etc.) within extensive AI and HPC cluster settings
  • Background with at scale GPU systems in general, encompassing performance testing, AI benchmarking, and more

What the JD emphasized

  • datacentre power, cooling, and MEP requirements
  • AI and HPC GPU infrastructure