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.
