NVIDIA is looking for Senior Customer Success/Partnership Solutions Architect to join its NVIDIA Infrastructure Specialist Team. Academic and commercial groups around the world are using NVIDIA products to redefine deep learning and data analytics, and to power data centers. We are building many of the largest and fastest AI/HPC systems in the world! We are looking for someone with the ability to work on a dynamic customer focused team that requires excellent communication skills.
This role will be interacting with customers, partners and internal teams, to analyze, define and implement large scale Networking projects. The scope of these efforts includes a combination of Networking, System Design and Automation and being the face to the customer!
What you'll be doing:
Lead the hands-on analysis, optimization, and performance tuning of complex GPU-accelerated systems and AI workloads, ensuring high availability and efficiency across customer data centers.
Serve as a senior technical authority on NVIDIA technologies, contributing to architecture reviews and guiding infrastructure decisions at scale.
Establish and refine monitoring and optimization methodologies using analytics, telemetry, and automation to detect bottlenecks and improve infrastructure resiliency.
Join post-deployment reviews, incident retrospectives, and sessions to craft the customer experience and provide insights into NVIDIA’s infrastructure strategy.
Complete and lead complex technical projects from initial design through implementation and continuous improvement, ensuring alignment to SLAs and mitigation of technical risks.
Support business growth by identifying AI infrastructure opportunities in cloud and enterprise environments and driving technical initiatives that showcase NVIDIA’s leadership in this space.
What we need to see:
10+ years of experience in large-scale data center service operations with a focus on infrastructure.
BS/MS/PhD or equivalent experience in Computer Science, Electrical/Computer Engineering, Physics, Mathematics, or related fields.
Strong analytical, solving problems, and decision-making skills, capable of identifying root causes, driving continuous improvement, and delivering resilient technical solutions.
Strong communication, time management, and organizational skills, with the ability to lead complex projects, guide technical teams.
Preferred certifications in data center, server, or networking technologies, and a willingness to travel up to 25% for customer engagements and team collaboration.
Proficiency in system-level aspects, encompassing Operating Systems, Linux kernel drivers, GPUs, NICs, and hardware architecture.
Shown expertise in cloud orchestration software and job schedulers, including platforms like Kubernetes, Docker Swarm, and HPC-specific schedulers such as Slurm.
Familiarity with cloud-native technologies and their integration with traditional infrastructure is essential.
Ways to stand out from the crowd:
Deep familiarity with AI infrastructure and workflows, including training/inference pipelines, MLOps/DevOps tools, containerization (Docker, Kubernetes), and large-scale system deployments.
Knowledge of data center infrastructure operations, including safety, security, environmental controls, and standard operating procedures.
Good interpersonal and collaboration skills, with the ability to lead discussions, influence outcomes, and build positive relationships with both internal and external collaborators.
Skills Required
- 10+ years of experience in large-scale data center service operations focused on infrastructure
- Bachelor's, master's, PhD, or equivalent experience in Computer Science, Electrical or Computer Engineering, Physics, Mathematics, or a related field
- Strong analytical, problem-solving, and decision-making skills
- Strong communication, time management, and organizational skills
- Ability to lead complex projects and guide technical teams
- Proficiency with operating systems, Linux kernel drivers, GPUs, NICs, and hardware architecture
- Expertise with cloud orchestration software and job schedulers, including Kubernetes, Docker Swarm, and Slurm
- Familiarity with cloud-native technologies and integration with traditional infrastructure
- Preferred certifications in data center, server, or networking technologies
- Deep familiarity with AI infrastructure, training and inference pipelines, MLOps, DevOps, containerization, and large-scale system deployments
- Knowledge of data center infrastructure operations, safety, security, environmental controls, and standard operating procedures
- Willingness to travel up to 25% for customer engagements and team collaboration
NVIDIA Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NVIDIA and has not been reviewed or approved by NVIDIA.
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Equity Value & Accessibility — Equity awards and a discounted ESPP are highlighted as core parts of total compensation, enabling employees to share in the company’s success. Stock-based compensation and the two-year lookback ESPP are consistently described as especially valuable.
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Healthcare Strength — Health coverage is portrayed as robust, with comprehensive medical, dental, and vision options alongside mental health support and on-site care resources. Employer HSA contributions and wellness perks reinforce the depth of the offering.
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Retirement Support — Retirement programs are depicted as strong, featuring a meaningful 401(k) match with Roth options and support for Mega Backdoor Roth contributions. These elements position long-term savings as a notable advantage of the total rewards package.
NVIDIA Insights
What We Do
NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”
