英伟达Senior Solutions Architect - CSP and CRISP System

• Partner with Sales, BD and CPM teams to land NVIDIA GPU and AI Infra technologies into top-tier Chinese CSP accounts, drive technical penetration and sustainable business growth. • Serve as the primary technical authority for NVIDIA GPU system and AI infrastructure solutions for Chinese CSPs, providing end-to-end consultation on GPU cluster architecture design, AI workload deployment, heterogeneous computing tuning, and full-stack software stack optimization. • Unlock Vera CPU + GPU co-optimization value for RL training and Agentic AI workloads, eliminate CPU-GPU data movement bottlenecks, optimize end-to-end agent training and reasoning pipeline latency and throughput for CSP AI factory scenarios. • Lead open-source system architecture contributions for NVIDIA AI infra stacks, upstream optimized patches for key open-source projects, build China-localized best practices and shape industry technical standards. • Conduct in-depth GPU workload bottleneck analysis, implement system-level, kernel-level and framework-level tuning for AI training, inference, RL and gaming workloads, deliver production-ready reference designs and tuning guidelines for CSP mass deployment. • Act as the key technical liaison between Chinese CSP customers and NVIDIA global engineering, product and R&D teams, collect high-value local workload requirements, drive product roadmap iteration, and ensure full compliance with NVIDIA global technical policies and export compliance rules. • Lead technical workshops, hands-on training, PoC and production pilot projects for key CSP accounts, quantify and demonstrate GPU/AI Infra business value, accelerate technology adoption and large-scale replication. • Monitor cutting-edge industry trends including Agentic AI, LLM inference optimization, cloud gaming AI, and next-gen data center system architectures, output strategic technical insights to support team and product strategy formulation. • Mentor junior SA team members, standardize CSP technical engagement and solution delivery processes, and drive the precipitation of high-value technical best practices.

• Work with Sales, BD and CPM team to introduce NVIDIA technologies into assigned accounts and grow business accordingly. • Serve as the primary technical authority on CPU technologies for NVIDIA’s Chinese CSP customers, providing expert consultation on CPU selection, architecture design, and integration with NVIDIA’s AI infrastructure (including Grace/Vera CPUs and NVL72 platforms). • Lead CPU-focused technical engagements with CSPs, collaborating with their R&D, infrastructure, and AI teams to understand workload requirements (e.g., AI data preprocessing, HPC, distributed computing) and design optimized CPU-GPU integrated solutions. • Drive CPU performance optimization for CSP workloads, conducting in-depth analysis of bottlenecks, implementing tuning strategies (including SIMD instruction set optimization and low-level intrinsics), and delivering reference implementations to unlock full platform potential. • Act as a liaison between CSP customers and NVIDIA’s global engineering, product, and R&D teams, advocating for customer-specific CPU requirements, providing feedback on product roadmaps, and ensuring alignment with NVIDIA’s technical strategy and export compliance guidelines. • Lead technical workshops, training sessions, and proof-of-concept (PoC) projects for CSPs, demonstrating the value of NVIDIA’s CPU-integrated solutions and enabling customer teams to effectively leverage these technologies. • Monitor industry trends in CPU technology, data center architectures, and CSP workload evolution, providing strategic insights to internal teams to enhance NVIDIA’s CPU-related products and solutions for the Chinese market. • Mentor junior technical team members, share CPU expertise, and drive best practices in CSP technical engagement and solution delivery.

• Work with sales to introduce NVIDIA technologies and products. • Account owner to promote products to customers, and bring feedback to product team. • Private or public workshops to illustrate and output NVIDIA’s offerings in details. • Debugging, tuning, testing during qualification, POC, integration and pilot. • Build good relationship with all levels of customers and become a trusted advisor. • Discover opportunities and guide customers to suitable solution. • Share knowledge across teams.

• Primary responsibilities will include building AI/HPC infrastructure for new and existing customers. • Support operational and reliability aspects of large-scale AI clusters, focusing on performance at scale, real-time monitoring, logging, and alerting. • Engage in and improve the whole lifecycle of services—from inception and design through deployment, operation, and refinement. • Maintain services once they are live by measuring and monitoring availability, latency, and overall system health. • Provide feedback to internal teams such as opening bugs, documenting workarounds, and suggesting improvements.