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Solutions Architect - NVIDIA AI Cloud Partners and Datacentre Infrastructure

Role overview

Qualifications

  • BS/MS/PhD in Mechanical/Electrical Engineering or other Engineering fields or equivalent experience
  • 8+ years in Solution Engineering or similar roles working directly with partners and customers
  • At least one of the following datacenter certifications: ATD, CDCAP, CDCDP, CDCEP, CDCMP, CDCSP
  • Practical expertise in datacentre design, development, and execution for AI and HPC

Responsibilities

  • Work closely with NVIDIA Cloud Partners to design, implement, and operationalise NVIDIA's hardware and software solutions
  • Serve as the primary technical contact for customers throughout the lifecycle of GPU cloud infrastructure
  • Conduct regular technical meetings to discuss project details, features, and datacentre-related challenges
  • Advise customers on trends and technologies in datacentre design and ensure compliance with standards

Key facts

Other skills

  • Time Management
  • Communication

About the company

NVIDIA logo

NVIDIA

Semiconductors

Since its founding in 1993, NVIDIA (NASDAQ: NVDA) has been a pioneer in accelerated computing. The company’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined computer graphics, ignited the era of modern AI and is fueling the creation of the metaverse. NVIDIA is now a full-stack computing company with data-center-scale offerings that are reshaping industry.

Company details

Company typeXLarge
IndustrySemiconductors
Company size10001

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Job description

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world.

We are seeking a skilled Solutions Architect with a strong emphasis on datacentre power, cooling, and MEP (Mechanical, Electrical, and Plumbing) requirements to support the deployment of advanced AI and HPC GPU infrastructure. Are you keen to join a team that brings GenAI, AI, and ML hardware and software technologies into real-world production, with a particular focus on the unique challenges of large-scale datacentre environments? In this role, you will collaborate closely with customers to assess and address the critical power distribution, cooling strategies, and MEP integration needed for next-generation GPU infrastructure. As part of the NVIDIA solutions architecture team, you’ll guide strategic customers through the complexities of datacentre design, ensuring robust, efficient, and scalable solutions while providing valuable feedback to business and engineering teams to shape product and infrastructure strategy.

What you'll be doing:

  • 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.

  • 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.

  • 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.

  • 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.

  • 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.

  • Prepare and deliver technical content to customers, including presentations and workshops, with an emphasis on datacentre best practices, power and cooling optimisation, and MEP requirements for large-scale GPU deployments.

  • Analyse and develop joint solutions to address customer performance and scaling issues, including troubleshooting datacentre power and cooling bottlenecks and improving infrastructure reliability.

  • Advise customers on the latest trends and technologies in datacentre design, including modular construction, efficient power management, advanced cooling techniques, and MEP innovations to support next-generation AI and HPC hardware.

  • Collaborate with engineering and business teams to provide feedback and recommendations for future NVIDIA products and infrastructure, focusing on datacentre power, cooling, and MEP enhancements.

  • Support customers in compliance with datacentre standards and regulations related to electrical, mechanical, and environmental requirements, ensuring safe and sustainable GPU infrastructure deployments.

What we need to see:

  • BS/MS/PhD in Mechanical/Electrical Engineering, or other Engineering fields or equivalent experience.

  • 8+ years in Solution Engineering (or similar Sales Engineering, Cloud Engineering) working directly with partners and customers.

  • Motivation and skills to own and drive technical engagements with customers throughout full customer life-cycle.

  • At least one of the following datacenter certifications ATD, CDCAP, CDCDP, CDCEP, CDCMP, CDCSP is requested

  • 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.

Ways to stand out from the crowd:

  • 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.

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Marcus Rivera

Chief Revenue Officer

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