Senior Software and System Architect

Posted 3 Days Ago
Be an Early Applicant
4 Locations
In-Office
Senior level
Artificial Intelligence • Computer Vision • Hardware • Robotics • Metaverse
The Role
Lead software and system architecture for next-generation DPU/SmartNIC management, QoS, telemetry, and observability. Define end-to-end control flows, interfaces, APIs, telemetry requirements, and architecture specs. Collaborate with hardware, firmware, drivers, validation, product, and customers through pre-silicon design, bring-up, and production readiness to ensure performance, diagnosability, and integration in large-scale AI and cloud datacenter environments.
Summary Generated by Built In

NVIDIA is looking for an outstanding Senior Networking Software Architect to join the NIC/DPU Software and Firmware Architecture group. In this role, you will help define the next generation of NVIDIA datacenter and AI networking platforms, with focus on DPU management, QoS, performance, telemetry, and software architecture across stacks. You will work closely with hardware designers, firmware/kernel driver teams, system engineers, validation, product management and customers. The role spans early architecture definition, pre-silicon design, bring-up, and production readiness for large-scale AI and cloud datacenter deployments. 

What You’ll Be Doing: 

  • Own software and system architecture for next-generation DPU management, QoS, performance, telemetry, and observability features. 

  • Define end-to-end control and management flows across DOCA, host drivers, embedded firmware, BMC, management controllers and external management systems. 

  • Specify telemetry and observability requirements, including counters, logs, traces, events, health monitoring, debug data, and streaming telemetry. 

  • Define management interfaces and APIs for configuration, provisioning, lifecycle operations, diagnostics, and field serviceability. 

  • Write clear architecture specifications, interface definitions, flow diagrams, and design documents for software, firmware, and system teams. 

  • Partner with R&D teams to translate high-level architecture into implementable designs and guide features through development, validation, silicon bring-up, and production. 

  • Analyze system performance bottlenecks, interoperability issues, telemetry gaps, and customer-reported issues, then feed learnings into future architecture. 

  • Collaborate with system and cluster architects to ensure NIC/DPU features fit end-to-end AI datacenter and cloud networking designs. 

What We Need To See: 

  • B.Sc. or M.Sc. in Computer Engineering, Computer Science, Electrical Engineering, or equivalent experience. 

  • 9+ years of experience in networking, system software, embedded software, firmware, or datacenter infrastructure. 

  • Proven experience in software architecture, or technical leadership roles. 

  • Deep understanding of networking concepts and protocols such as Ethernet, TCP/IP, RDMA/RoCE, congestion control, QoS, virtualization overlays, and traffic management. 

  • Strong background with DPUs, SmartNICs, or other high-performance networking devices. 

  • Experience with system management, provisioning, monitoring, telemetry, diagnostics, or lifecycle-management flows. 

  • Familiarity with management protocols and frameworks such as Redfish, PLDM, MCTP, IPMI, gNMI, SNMP, Netconf, REST, or gRPC-based APIs. 

  • Ability to lead cross-functional architecture discussions across software, firmware, hardware, validation, product, and customer-facing teams. 

  • Excellent written and verbal communication skills, including the ability to create clear architecture documents and present trade-offs. 

Ways To Stand Out From The Crowd: 

  • Experience defining software architecture for DPU products, including management, telemetry, QoS, performance, security, virtualization, or offload features. 

  • Hands-on background with Linux networking, device drivers, firmware, embedded Linux, BMC software, DOCA, DPDK, OVS or Kubernetes networking. 

  • Experience with performance counters, profiling tools, eBPF, Prometheus, Grafana, dashboards, heat maps, or large-scale telemetry systems. 

  • Experience in defining and developing GAI-based analysis tools to extract insights from telemetry data and streams. 

  • Background in RAS, diagnosability, serviceability, field failure analysis, production debug, or customer escalation handling. 

NVIDIA is widely considered one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the industry working with us, and we are building the networking platforms that power the AI revolution. If you are passionate about NICs, DPUs, system software, and large-scale AI networking, and you want to shape the management, telemetry, QoS, and performance architecture of future NVIDIA platforms, we want to hear from you.

Skills Required

  • B.Sc. or M.Sc. in Computer Engineering, Computer Science, Electrical Engineering, or equivalent experience
  • 9+ years of experience in networking, system software, embedded software, firmware, or datacenter infrastructure
  • Proven experience in software architecture or technical leadership roles
  • Deep understanding of networking concepts and protocols: Ethernet, TCP/IP, RDMA/RoCE, congestion control, QoS, virtualization overlays, traffic management
  • Strong background with DPUs, SmartNICs, or other high-performance networking devices
  • Experience with system management, provisioning, monitoring, telemetry, diagnostics, or lifecycle-management flows
  • Familiarity with management protocols/frameworks: Redfish, PLDM, MCTP, IPMI, gNMI, SNMP, Netconf, REST, or gRPC-based APIs
  • Ability to lead cross-functional architecture discussions across software, firmware, hardware, validation, product, and customer teams
  • Excellent written and verbal communication skills and ability to create clear architecture documents
  • Experience defining software architecture for DPU products, including management, telemetry, QoS, performance, security, virtualization, or offload features
  • Hands-on background with Linux networking, device drivers, firmware, embedded Linux, BMC software, DOCA, DPDK, OVS or Kubernetes networking
  • Experience with performance counters, profiling tools, eBPF, Prometheus, Grafana, dashboards, or large-scale telemetry systems
  • Experience defining and developing GAI-based analysis tools for telemetry data and streams
  • Background in RAS, diagnosability, serviceability, field failure analysis, production debug, or customer escalation handling

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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