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Solution Architect - Agentic AI - CSP

NVIDIA· Architect, Solutions
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Beijing, China, Shenzhen, Chinaon-sitePosted 1mo ago

About the role

AI-focused Solutions Architect specializing in Agentic AI inference to design, optimize, and scale large-scale inference systems on NVIDIA accelerated computing platforms, collaborating with cloud providers, AI platform teams, and NVIDIA internal groups.

Responsibilities

  • Work with customers to design, deploy, and optimize large-scale LLM and Agentic AI inference systems on NVIDIA accelerated computing platforms.
  • Analyze end-to-end inference workloads and identify opportunities to improve latency, throughput, scalability, resource utilization, and cost efficiency.
  • Explore and develop solutions for emerging Agentic AI inference challenges, including KV cache management, intelligent routing and scheduling, distributed or disaggregated serving, heterogeneous inference, and large-scale model parallelism.
  • Build proof-of-concepts, performance studies, and reference solutions to validate new architectures and demonstrate the value of NVIDIA technologies in real-world AI workloads.
  • Partner with NVIDIA Engineering, Product, Sales, and Business Development teams to solve customer problems, provide product feedback, and help shape technical strategies for strategic AI infrastructure opportunities.

Qualifications

  • MS or PhD in Electrical Engineering, Computer Science/Engineering, Mathematics, Physics, or a related field, or equivalent practical experience.
  • 3+ years of relevant experience in large language models, AI inference, distributed AI systems, or related areas, with hands-on experience in system design, performance optimization, or large-scale AI workloads.
  • Strong understanding of modern AI systems and the ability to analyze performance across models, software frameworks, compute, memory, communication, and infrastructure.
  • Strong programming and problem-solving skills, with experience using common AI frameworks and tools. Proficiency in using AI tools or agents to improve engineering productivity is highly valued.
  • Clear and structured thinking, strong technical communication skills, and the ability to work effectively with both engineering teams and senior technical stakeholders.

Skills

Required:Large language models (LLMs)AI inferenceDistributed AI systems
Last updated Aug 28, 2026. Interested? Apply on the company site.

About NVIDIA

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NVIDIA invents the GPU and drives advances in AI, HPC, gaming, creative design, autonomous vehicles, and robotics.

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