N

NVIDIA

Designs the chips and software that power AI

Senior Solutions Architect - CSP System

Pre-Sales Solution EngineeringConfirmed live in the last 24 hours
Full-timeNo salary listedIn-person

About the Job

Requirements

  • A Bachelor's, Master's, or PhD degree in Computer Science, Computer Engineering, Electrical Engineering, Networking, or a related field; equivalent industry experience is highly valued.
  • At least 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 experience in North-South dataplane design, API Gateway systems, or service mesh infrastructure.
  • Deep understanding of datacenter North-South network architecture, including load balancing, reverse proxies, API Gateways such as Envoy, Nginx, and HAProxy, service meshes such as Istio and Cilium, and cloud-native networking, including CNI, the Kubernetes networking model, and Gateway API.
  • Strong programming proficiency in C/C++ and Python; familiarity with dataplane programming such as DPDK, eBPF/XDP, P4, or DOCA; network protocol stacks including TCP/IP, RDMA, HTTP/2, and gRPC; and high-performance packet processing.
  • Hands-on experience with major Chinese CSPs or global hyperscalers on network infrastructure projects, including in-depth knowledge of their cloud networking architecture, traffic management mechanisms, and North-South dataplane evolution.
  • Understanding of AI inference serving architecture such as vLLM, TensorRT-LLM, and Triton, and of how network infrastructure supports inference traffic patterns including prefill/decode disaggregation, KV-Cache transfer, token streaming, and multi-model Agent orchestration.
  • Ability to explain complex network systems and DPU acceleration technologies to technical engineers, architecture teams, and business stakeholders.
  • Ability to collaborate cross-functionally in a global matrix team and prioritize multiple technical projects under fast-paced business demands.
  • Hands-on engineering capability and ability to independently own end-to-end technical project delivery.
  • Ability to sustain high-quality technical output for long-term strategic CSP projects.

Responsibilities

  • Partner with Sales, BD, and CPM teams to land NVIDIA BlueField DPU and DOCA Agent networking technologies in top-tier Chinese CSP accounts, drive technical penetration, and grow business in the Agent infrastructure market.
  • Serve as the primary technical authority for NVIDIA Agent North-South network infrastructure solutions for Chinese CSPs, providing end-to-end consultation on DPU-accelerated API Gateway architecture, Agent traffic routing and orchestration, North-South telemetry, and inline AI inspection pipeline design.
  • Design and deliver BF4/DOCA 3.0 Agent-specific North-South solutions, including hardware-accelerated Agent API Gateways, inline token-level Agent traffic metering, multi-agent communication mesh acceleration, and North-South 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 including Kubernetes Gateway API, Envoy xDS, Cilium, and eBPF, build China-localized best practices, and shape technical standards for Agent networking.
  • Analyze North-South traffic patterns for Agentic AI workloads including tool-calling, RAG retrieval, multi-agent orchestration, and human-agent interaction; implement DPU-level and DOCA-level dataplane optimizations; and deliver production-ready reference designs and tuning guidelines for CSP mass deployment.
  • Act as the technical liaison between Chinese CSP customers and NVIDIA Networking BU global engineering, product, and R&D teams; gather local Agent networking requirements, drive BlueField/DOCA product roadmap iteration, and align with NVIDIA global technical policies.
  • Lead technical workshops, hands-on training, PoC and production pilot projects for key CSP accounts; quantify and demonstrate the business value of DPU-accelerated Agent networking, including latency reduction, throughput improvement, and TCO savings versus software-only solutions; and accelerate technology adoption and replication.
  • Monitor industry trends in Agentic AI infrastructure, LLM serving network topology, MCP/A2A protocol standardization, disaggregated inference architecture, and cloud-native service mesh; provide technical insights for team and product strategy.
  • Mentor junior SA team members on DPU and networking domains, standardize CSP Agent networking technical engagement and solution delivery processes, and develop technical best practices.

Desired Qualifications

  • Familiarity with NVIDIA networking products including BlueField DPU, ConnectX SmartNIC, DOCA SDK, Spectrum switches, and NetQ.
  • Hands-on experience with BlueField DPU/DOCA dataplane development, including DPA programming, hardware steering rules, and crypto/compression offload for North-South traffic.
  • In-depth experience building or operating large-scale API Gateway/L7 proxy systems at CSP-level traffic volumes of 1M+ RPS, with optimization for latency-sensitive AI inference traffic.
  • Contributions to cloud-native networking open-source projects such as Envoy, Cilium, Istio, Kubernetes SIG-Network, or Gateway API, with public upstream records.
  • Understanding of Agentic AI infrastructure patterns, including MCP, A2A, LangChain/CrewAI/AutoGen runtime architecture, Agent tool-calling traffic patterns, and multi-agent communication topology.
  • Experience designing disaggregated inference serving architectures where networking is critical, including prefill-decode separation, remote KV-Cache access over RDMA/RoCE, and North-South token routing for mixture-of-experts models.
  • Familiarity with DPU-based security and observability, including inline AI traffic inspection, token-level metering and billing, Agent identity/authentication offload, and zero-trust micro-segmentation for multi-tenant Agent platforms.
  • A track record of independently leading CSP network infrastructure PoCs, pilot verification, and large-scale production deployments with measurable latency, throughput, or TCO outcomes.
  • Familiarity with semiconductor and data center technology export compliance requirements in the China market.

About the Company

NVIDIA

Designs the chips and software that power AI

NVIDIA designs the chips and software that power artificial intelligence and sells complete data center systems to cloud providers, AI labs, and other businesses, along with GeForce graphics cards for gamers. Its GPUs, chips that perform thousands of calculations at once, became the main hardware for AI after researchers used them to train the AlexNet image-recognition model in 2012. NVIDIA connects many GPUs with its own processors and networking gear into servers and rack-sized computers, and developers program them through its CUDA software. These systems bring in most of its sales, and it also makes chips for cars and robots. Jensen Huang co-founded NVIDIA in 1993, and it is based in Santa Clara, California.

Company size
10,001+
Company stage
IPO
Headquarters
Santa Clara, CA
Founded
1993

Recently Posted Jobs

Explore more opportunities at NVIDIA

See more jobs