英伟达Senior Data Center Ethernet Network Engineer

We are looking for a Senior Account Manager for Automotive Data Center to create, drive and accelerate growth of NVIDIA business in automotive segment. You are responsible to develop our business with large automotive customers. You will work closely with many groups within NVIDIA, including Partner team, Solutions Architects, Software Developers, HW & SW Architecture, and headquarter product teams to develop right business strategy for China large auto customers. In this role you can expect high visibility with NVIDIA senior executives, given the strategic priority for developing NVIDIA computing platform for autonomous driving in major China automotive makers. What you’ll be doing: • Drive NVIDIA revenue in large auto accounts • Engage with various NVIDIA technology partners and identify areas of collaboration. Identify complementary technologies needed to build complex solutions using our computing platforms. • Create go-to-market execution w/ cross functional teams • Prioritize and report on key business metrics to measure and guide global industry teams. • Influence and align with sales and customer teams to understand customer requirements and build a scale out plan for target market technologies • Generating technology trends and market analysis • Represent and evangelize NVIDIA solutions at key industry events

- Collaborate with internal stakeholders to define project design criteria and develop the Basis of Design (BOD). - Manage consultants to implement the project from schematic design through design development to construction documents. - Oversee the design-build contractor to ensure the project meets the business and technical needs defined in the BOD. - Provide construction administrative support to the project manager during construction, including tasks such as responding to RFIs, issuing technical bulletins, reviewing submittals and shop drawings, and conducting source inspections at vendor factories. - Work with the Commissioning (Cx) Agent, contractors, and operations team to complete various levels of startup and commissioning, including Integrated System Testing (IST). This includes reviewing Cx scripts, closing critical punch-list items before IST, and tracking/closing global commissioning QA/QC items. - Collaborate with HQ and data center operations teams to incorporate the latest lessons learned from operations into new greenfield design projects. - Review engineering calculations from consultants and conduct independent engineering and cost analyses. - Research new designs, materials, and construction methods for data center HVAC equipment and related components. - Travel to data center sites for engineering studies, mechanical systems audits, startup testing, and full commissioning as required. - Provide guidance to design consultants and installation contractors, ensuring the quality of installed work. - Take ownership of tasks and work proactively to achieve goals with good team spirit. - Respond to emergencies on an as-needed basis.

AI Agent Engineering • Design, develop, and deploy production-grade AI agent systems, including multi-agent orchestration, tool-use frameworks, memory management, and API integration — ensuring reliability, scalability, and maintainability • Build and optimize Retrieval-Augmented Generation (RAG) pipelines: document ingestion, chunking strategy, embedding, vector search, and re-ranking to maximize LLM grounding quality • Support LLM adaptation to WWGS business domains through prompt engineering, context injection, fine-tuning signal curation, and systematic prompt evaluation frameworks • Develop automated knowledge base construction and real-time data access capabilities (Data Agent, MCP server/client) to connect AI agents with live business data • Design and implement LLM evaluation pipelines to systematically assess agent output quality, hallucination risk, and business impact Data Engineering • Design and implement end-to-end data pipelines (batch and streaming) for data collection, transformation, and storage — supporting both AI application and analytics use cases • Build and maintain integration layer data models that serve as a unified, AI-ready data foundation across WWGS domains • Develop automated data quality monitoring, alerting, and observability tooling to ensure pipeline reliability and data trustworthiness • Integrate multi-source data (seller behavior, transaction logs, off-platform signals, AI outputs) into a coherent, governed data layer • Establish data standardization and governance policies ensuring consistency, accuracy, and compliance across AI and BI consumption layers Technical Leadership • Provide technical guidance on AI-data architecture decisions; define best practices for the team's AI agent and data engineering stack • Collaborate cross-functionally with Product, Operations, and Science teams to translate business requirements into scalable technical solutions • Mentor junior engineers and conduct design reviews; raise the technical bar across the team

• Collaborate with BIE,DE, PM, CSM to research, design, develop, and evaluate generative AI solutions to address Global Selling challenges. • Interact with stakeholders directly to understand their business problems, aid them in implementation of generative AI solutions, brief stkaholders and guide them on adoption patterns and paths to production • Create and deliver best practice recommendations, tutorials, blog posts, sample code, and presentations adapted to technical, business, and executive stakeholder