Senior Solutions Architect – Data Center Infrastructure

This is a fully remote position, open to applicants in California, +2 more states.

📋 Description

• Assist in designing and scaling high-performance, distributed AI infrastructure, whether on-premises or in the cloud, utilizing the latest NVIDIA GPU supercomputers for both new and existing clients.

• Serve as a technical expert on GPU and networking products, providing direct support to sales account managers to secure design victories.

• Deliver technical and onsite assistance to tackle complex hardware and software issues, with an emphasis on deep learning inference.

• Gather, maintain, and evaluate intricate deployment data and logs to gauge product performance, identify technical obstacles, and guide customers towards overcoming challenges.

• Proactively establish and cultivate technical relationships with engineers and architects at key customer accounts.

• Recognize customer architectures and critical product requirements in the CSP/OEM AI sector to effectively implement NVIDIA's solutions.

• Create technical solutions that include hardware and software demonstrations as well as example system designs.

• Provide technical and sales training to both direct sales teams and channel partners.

⛳️ Requirements

• BS/MS/PhD in Electrical/Computer Engineering, Computer Science, Physics, or other Engineering disciplines, or equivalent experience.

• Over 8 years of relevant experience in the high-tech electronics sector, specifically in system design or technical customer support roles.

• Technical capability to delve into logs and deployment data, guiding customers to resolve technical challenges.

• Strong analytical and problem-solving skills.

• Ability to thrive in a dynamic and constantly changing environment.

• Exceptional written and verbal communication skills in English, with the ability to collaborate effectively with management and engineering teams.

• Experience in a Hyperscaler or Cloud Service Provider (CSP) setting, or substantial engagement with them as a strategic ally.

• Practical experience with NVIDIA hardware (e.g., ARM CPU, H100, GB200) and software libraries, along with an understanding of performance optimization and error diagnostics.

• Proven history of taking a product from the pilot stage to large-scale deployment in a data center environment.

• Familiarity with NVIDIA systems technology such as NCCL, DCGM, and UFM.

• Understanding of Embedded Linux Systems, APIs, and similar embedded operating systems.

🏝️ Benefits

• Equity

• Benefits