NVIDIA is the world leader in computer graphics, artificial intelligence, and accelerated computing. For over 25 years, we have been at the forefront of research and engineering around the greatest advances in technology. Our history of innovation drives us to solve the worlds hardest problems.
NVIDIA is looking for Senior Industry SA/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 social 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.
Engage with NVIDIA strategic customers to drive AI infrastructure initiatives, support deployment success, and influence long-term platform adoption.
Serve as a senior technical authority on NVIDIA GPU, DPU, and networking technologies, contributing to architecture reviews and guiding infrastructure decisions at scale.
Collaborate with internal Engineering, Product, and Sales teams to align customer deployments with NVIDIA’s technology roadmap and business objectives.
Establish and refine monitoring and optimization methodologies using analytics, telemetry, and automation to detect bottlenecks and improve infrastructure resiliency.
Participate in post-deployment reviews, incident retrospectives, and strategic planning sessions to shape the customer experience and feed 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 performance, backed by a Bachelor’s, Master’s, or PhD in Computer Science, Engineering, or a related field.
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, and meet important metrics.
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.
Demonstrated 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 crucial.
Proficiency in both Japanese and English, with the ability to communicate complex technical topics clearly across multicultural teams and with customers.
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.
Proven expertise in scaling complex systems, with deep experience in automation, orchestration, and performance optimization across compute, storage, and networking layers.
Good interpersonal and collaboration skills, with the ability to lead discussions, influence outcomes, and build positive relationships with both internal and external collaborators.
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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.”
