英伟达Senior Technical Systems AI Architect – Agentic AI

aNVIDIA’s Solutions Architect team is looking for a software-focused Solutions Architect to drive adoption of next-generation AI infrastructure across NVIDIA CPU platforms and LPU-based inference systems. This role will focus on NVIDIA CPUs, including Grace, Vera, and future CPU generations, and on LPU platforms and LPX-class systems used to accelerate large language model inference and other latency-sensitive generative AI workloads. We are looking for someone who understands that AI efficiency is a full-stack challenge spanning model architecture, runtime, compiler, serving framework, host software, memory movement, and workload partitioning across CPU, GPU, and LPU.As a Solutions Architect, you will be the first line of technical expertise between NVIDIA and our customers for CPU- and LPU-centric AI system design. You will help customers understand how NVIDIA CPUs and LPU-based systems can improve the efficiency, latency, throughput, and total cost of their AI workloads, especially when deployed alongside NVIDIA GPUs in heterogeneous production environments. Your work will range from proof-of-concept development and software stack optimization to technical leadership with customer architects, engineering teams, and senior decision makers. You will engage directly with developers, ML engineers, researchers, platform architects, and IT leaders to identify bottlenecks, design optimization strategies, and build deployable reference architectures. You will also work closely with NVIDIA engineering, product, and field teams to translate customer needs into platform feedback, solution patterns, and roadmap inputs. What you’ll be doing: • Evangelize NVIDIA CPU platforms, including Grace, Vera, and future generations, as well as LPU-based systems and LPX-class platforms, with a strong focus on AI software stacks and workload efficiency. • Help customers design and optimize AI workloads across CPU, GPU, and LPU, improving latency, throughput, utilization, and overall cost efficiency. • Analyze and tune LLM and generative AI pipelines across serving, runtime, memory, I/O, batching, scheduling, and orchestration layers. • Build proof-of-concepts, reference architectures, and technical guidance in partnership with Engineering, Product, and Sales teams. • Establish trusted technical relationships with customer architects, infrastructure teams, and senior leaders, becoming a strategic advisor for heterogeneous AI system design.

NVIDIA’s Solution Architect team is looking for a AI-focused Solution Architect with expertise in Large Language Model, generative AI, agentic AI, or recommender system. We work with the most exciting computing hardware and software, driving the latest breakthroughs in artificial intelligence. We need individuals who can enable customer productivity and develop lasting relationships with our technology partners, making NVIDIA an integral part of end-user solutions. We are looking for someone always thinking about artificial intelligence, someone who can maintain constructive collaboration in a fast paced, rapidly evolving field, someone able to coordinate efforts between corporate marketing, industry business development and engineering. You will be working with the latest AI architecture coupled with the most advanced neural network models, changing the way people interact with technology.As a Solutions Architect, you will be the first line of technical expertise between NVIDIA and our customers. Your duties will vary from working on proof-of-concept demonstrations, to driving relationships with key executives and managers to evangelize accelerated computing. Dynamically engaging with developers, scientific researchers, data scientists, IT managers and senior leaders is a meaningful part of the Solutions Architect role and will give you experience with a range of partners and concerns. What you’ll be doing: • Assisting field business development in guiding the customer build/extend their GPU infrastructures for AI. • Help customers build their large-scale projects, especially Large Language Model (LLM) projects. • Engage with customers to perform in-depth analysis and optimization to ensure the best performance on GPU architecture systems. This includes support in optimization of both training and inference pipelines. • Partner with Engineering, Product and Sales teams to develop, plan best suitable solutions for customers. Enable development and growth of product features through customer feedback and proof-of-concept evaluations. • Build industry expertise and become a contributor in integrating NVIDIA technology into Enterprise Computing architectures.

• 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.

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