Senior Solutions Architect, Customer Success and Partnership

In this role, you will lead hands-on analysis and optimization of GPU-accelerated systems and AI workloads in customer data centers. You will act as a senior technical authority, guiding architecture decisions at scale and shaping the customer experience post-deployment. You’ll establish analytics-driven monitoring, drive continuous improvement, and identify opportunities to showcase NVIDIA’s leadership in AI infrastructure. This position sits at the intersection of engineering, operations, and customer success, collaborating with customers, partners, and internal teams to deliver resilient solutions.

• Lead hands-on analysis, optimization, and performance tuning of GPU-accelerated systems and AI workloads for high availability and efficiency
• Serve as a senior technical authority on NVIDIA technologies, guiding infrastructure decisions at scale
• Develop monitoring and optimization methodologies using analytics, telemetry, and automation to detect bottlenecks and improve resiliency
• Participate in post-deployment reviews and incident retrospectives to improve customer experience and inform infrastructure strategy
• Plan and lead complex technical projects from design to implementation and continuous improvement, aligned with SLAs and risk mitigation
• Identify AI infrastructure opportunities in cloud and enterprise environments to support business growth and showcase NVIDIA leadership

• 10+ years of experience in large-scale data center service operations with a focus on infrastructure
• Bachelor's degree or higher in Computer Science, Electrical/Computer Engineering, Physics, Mathematics, or related fields
• Strong analytical, problem-solving, and decision-making skills with a track record of root-cause analysis and durable solutions
• Excellent communication, time management, and organizational abilities; capable of leading complex projects and guiding technical teams
• Willingness to travel up to 25% for customer engagements and team collaboration
• Proficiency in system-level aspects: OS, Linux kernel drivers, GPUs, NICs, and hardware architecture
• Experience with cloud orchestration software and job schedulers (Kubernetes, Docker Swarm, Slurm); familiarity with cloud-native technologies
• Familiarity with data center operations, safety, security, environmental controls, and standard operating procedures

• strong communication
• leadership
• collaboration
• GPU-accelerated systems
• AI workloads
• telemetry and automation