Senior Solutions Architect, CSP System

Posted 15 Days Ago
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2 Locations
In-Office
Senior level
Artificial Intelligence • Computer Vision • Hardware • Robotics • Metaverse
The Role
Leads NVIDIA BlueField DPU and DOCA networking solutions for major Chinese cloud service providers. Designs North-South network architectures, API Gateway acceleration, traffic orchestration, telemetry, inference networking, and dataplane optimizations for Agentic AI workloads. Partners with sales, customers, and global engineering teams; leads workshops, proofs of concept, pilots, deployments, open-source contributions, and technical roadmap development. Mentors solution architect teams and delivers measurable latency, throughput, and total-cost improvements.
Summary Generated by Built In

As a Senior Agent Infrastructure Network Expert focusing on Cloud Service Providers (CSPs) in China, you will be a core technical pillar in NVIDIA’s CSP SA team, responsible for driving DPU/SmartNIC-based North-South network architecture strategy, Agent-aware traffic optimization, and high-value customer engagement for next-generation Agentic AI datacenter networking. You will work closely with major Chinese CSPs to address their critical demands on Agent API Gateway acceleration, N-S inference traffic orchestration, multi-agent communication infrastructure, and cloud-native network dataplane offload. You will accelerate the mass deployment and performance maximization of NVIDIA BlueField DPU and DOCA software stacks for Agentic AI N-S networking use cases, and bridge technical gaps between CSP Agent infrastructure evolution and NVIDIA global networking product roadmap. This role requires deep expertise in datacenter N-S network architecture, DPU/SmartNIC dataplane programming, cloud-native networking, and AI inference serving infrastructure, with strong capability to deliver high-value technical outcomes for hyperscale Agentic AI workloads.

What you'll be doing:

  • Partner with Sales, BD and CPM teams to land NVIDIA BlueField DPU and DOCA Agent networking technologies into top-tier Chinese CSP accounts (Tencent, Baidu primary), drive technical penetration and sustainable business growth in the emerging Agent infrastructure market.

  • Serve as the primary technical authority for NVIDIA Agent N-S network infrastructure solutions for Chinese CSPs, providing end-to-end consultation on DPU-accelerated API Gateway architecture, Agent traffic routing & orchestration, N-S telemetry, and inline AI inspection pipeline design.

  • Design and deliver BF4/DOCA 3.0 Agent-specific N-S solutions including: hardware-accelerated Agent API Gateway (replacing Envoy/Nginx software dataplanes), inline token-level Agent traffic metering, multi-agent communication mesh acceleration, and N-S KV-Cache access optimization for disaggregated inference architectures.

  • Lead open-source network architecture contributions for NVIDIA Agent infrastructure stacks, upstream optimized integrations with cloud-native ecosystems (Kubernetes Gateway API, Envoy xDS, Cilium, eBPF), build China-localized best practices and shape industry technical standards for Agent networking.

  • Conduct in-depth N-S traffic pattern analysis for Agentic AI workloads (tool-calling, RAG retrieval, multi-agent orchestration, human-agent interaction), implement DPU-level and DOCA-level dataplane optimizations, deliver production-ready reference designs and tuning guidelines for CSP mass deployment.

  • Act as the key technical liaison between Chinese CSP customers and NVIDIA Networking BU (NBU) global engineering, product and R&D teams, collect high-value local Agent networking requirements, drive BlueField/DOCA product roadmap iteration, and ensure alignment with NVIDIA global technical policies.

  • Lead technical workshops, hands-on training, PoC and production pilot projects for key CSP accounts, quantify and demonstrate DPU-accelerated Agent networking business value (latency reduction, throughput improvement, TCO savings vs software-only solutions), accelerate technology adoption and large-scale replication.

  • Monitor cutting-edge industry trends including Agentic AI infrastructure patterns, LLM serving network topology evolution, MCP/A2A protocol standardization, disaggregated inference architecture, and next-gen cloud-native service mesh, output strategic technical insights to support team and product strategy formulation. Mentor junior SA team members on DPU/networking domains, standardize CSP Agent networking technical engagement and solution delivery processes, and drive the precipitation of high-value technical best practices.

What we need to see:

  • Bachelor's/Master's/PhD degree in Computer Science, Computer Engineering, Electrical Engineering, Networking, or a related field; equivalent industry experience is highly valued.

  • 7+ years of hands-on experience in datacenter network architecture, cloud-native networking, DPU/SmartNIC development, or large-scale L4-L7 traffic management systems, with solid experience in North-South dataplane design, API Gateway systems, or service mesh infrastructure.

  • Deep understanding of datacenter N-S network architecture: load balancing, reverse proxy, API Gateway (Envoy, Nginx, HAProxy), service mesh (Istio, Cilium), and cloud-native networking (CNI, Kubernetes networking model, Gateway API).

  • Strong programming proficiency in C/C++ and Python; familiar with dataplane programming (DPDK, eBPF/XDP, P4, or DOCA), network protocol stacks (TCP/IP, RDMA, HTTP/2, gRPC), and high-performance packet processing. Proven hands-on experience working with major Chinese CSPs or global hyperscalers on network infrastructure projects, with in-depth knowledge of their cloud networking architecture, traffic management mechanisms, and N-S dataplane evolution. Understanding of AI inference serving architecture (vLLM, TensorRT-LLM, Triton) and how network infrastructure supports inference traffic patterns including: prefill/decode disaggregation, KV-Cache transfer, token streaming, and multi-model Agent orchestration. Excellent technical communication and presentation skills, capable of explaining complex network system and DPU acceleration technologies to technical engineers, architecture teams and business stakeholders.

  • Strong cross-functional collaboration capability, able to work efficiently in a global matrix team and prioritize multiple high-value technical projects under fast-paced business demands. Familiar with NVIDIA networking products (BlueField DPU, ConnectX SmartNIC, DOCA SDK, Spectrum switches, NetQ) is a significant plus. Hands-on engineering capability is mandatory; candidate must be result-oriented, self-driven and able to independently own end-to-end technical project delivery.Committed, proactive, and capable of sustaining high-quality technical output for long-term strategic CSP projects.

Ways to stand out from the crowd:

  • Hands-on experience with BlueField DPU / DOCA dataplane development, including DPA (Data Path Accelerator) programming, hardware steering rules, and crypto/compression offload for N-S traffic.

  • In-depth experience building or operating large-scale API Gateway / L7 proxy systems at CSP-level traffic volumes (1M+ RPS), with proven optimization for latency-sensitive AI inference traffic. Proven contribution to cloud-native networking open-source projects (Envoy, Cilium, Istio, Kubernetes SIG-Network, or Gateway API) with public upstream records.

  • Solid understanding of Agentic AI infrastructure patterns: MCP (Model Context Protocol), A2A (Agent-to-Agent) protocol, LangChain/CrewAI/AutoGen runtime architecture, Agent tool-calling traffic patterns, and multi-agent communication topology. Experience designing disaggregated inference serving architectures where network plays a critical role: prefill-decode separation, remote KV-Cache access over RDMA/RoCE, and N-S token routing for mixture-of-experts models.

  • Familiarity with DPU-based security and observability: inline AI traffic inspection, token-level metering and billing, Agent identity/authentication offload, and zero-trust micro-segmentation for multi-tenant Agent platforms.Proven track record of independently leading CSP network infrastructure PoC, pilot verification and large-scale production deployment projects with measurable business outcomes (latency, throughput, TCO).Familiar with semiconductor and data center technology export compliance requirements in China market.

Skills Required

  • Bachelor's, master's, or PhD degree in Computer Science, Computer Engineering, Electrical Engineering, Networking, or a related field, or equivalent industry experience
  • 7+ years of hands-on experience in datacenter network architecture, cloud-native networking, DPU/SmartNIC development, or large-scale L4-L7 traffic management systems
  • Experience with North-South dataplane design, API Gateway systems, or service mesh infrastructure
  • Deep understanding of load balancing, reverse proxies, API Gateways such as Envoy, Nginx, and HAProxy, service mesh, and cloud-native networking
  • Strong proficiency in C/C++ and Python
  • Familiarity with dataplane programming using DPDK, eBPF/XDP, P4, or DOCA
  • Knowledge of TCP/IP, RDMA, HTTP/2, gRPC, and high-performance packet processing
  • Hands-on experience with major Chinese cloud service providers or global hyperscalers on network infrastructure projects
  • Understanding of AI inference serving architecture, including vLLM, TensorRT-LLM, Triton, prefill/decode disaggregation, KV-Cache transfer, token streaming, and multi-model orchestration
  • Excellent technical communication and presentation skills
  • Strong cross-functional collaboration skills and ability to manage multiple technical projects in a global matrix team
  • Hands-on engineering capability and ability to independently own end-to-end technical project delivery
  • Experience with BlueField DPU, DOCA dataplane development, DPA programming, hardware steering, and crypto/compression offload
  • Experience operating large-scale API Gateway or L7 proxy systems at CSP traffic volumes of 1M+ requests per second
  • Public upstream contributions to Envoy, Cilium, Istio, Kubernetes SIG-Network, or Gateway API
  • Understanding of Agentic AI infrastructure, MCP, A2A, LangChain, CrewAI, or AutoGen
  • Experience designing disaggregated inference serving architectures, remote KV-Cache access over RDMA/RoCE, or N-S token routing
  • Familiarity with DPU-based security and observability, token metering, identity offload, and zero-trust micro-segmentation
  • Track record leading CSP network infrastructure proofs of concept, pilots, and production deployments with measurable business outcomes
  • Familiarity with semiconductor and data center technology export compliance requirements in China

NVIDIA Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NVIDIA and has not been reviewed or approved by NVIDIA.

  • Equity Value & Accessibility Equity awards and a discounted ESPP are highlighted as core parts of total compensation, enabling employees to share in the company’s success. Stock-based compensation and the two-year lookback ESPP are consistently described as especially valuable.
  • Healthcare Strength Health coverage is portrayed as robust, with comprehensive medical, dental, and vision options alongside mental health support and on-site care resources. Employer HSA contributions and wellness perks reinforce the depth of the offering.
  • Retirement Support Retirement programs are depicted as strong, featuring a meaningful 401(k) match with Roth options and support for Mega Backdoor Roth contributions. These elements position long-term savings as a notable advantage of the total rewards package.

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The Company
HQ: Santa Clara, CA
21,960 Employees
Year Founded: 1993

What We Do

NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”

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