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NVIDIA

Senior Software E2E Architect

NVIDIA is hiring a Senior Software E2E Architect. Level rates it ; you can apply on NVIDIA.

Level's read on this job

  • Level rates this role Builds AI ●●●●: the job is building AI systems.
  • The posting mentions Spectrum X, GPUs and system architecture among its tools and skills.
  • Level classes it as a senior role.
  • NVIDIA has 2,600+ other open roles on Level.

AI in this role

Define end-to-end system architectures for next-generation AI and accelerated computing platforms.

spectrum-xgpus
system-architecturedistributed-systemsnetworkingdeep-learninggpu-acceleration

NVIDIA is seeking a senior, hands-on End-to-End Architect to define and drive system architecture for next-generation AI and accelerated computing platforms. Join our E2E Architecture group, where we build large-scale solutions that bring together high-capacity communication systems, software, physical devices, and infrastructure.

In this role, you will own system-level architecture across multiple technologies and organizational boundaries. You will interpret product and business requirements to develop complete architectural solutions, identify gaps across system components, and drive technical alignment from early definition through productization and deployment.

 

What You’ll Be Doing:

  • Define end-to-end system architectures for Spectrum-X solutions, covering networking, software, hardware, infrastructure, and application integration.

  • Lead architecture tasks for the entire solution lifecycle, from requirements and system definition through implementation, validation, deployment, and optimization.

  • Collaborate with systems, software, model, networking, platform, and application teams to deliver integrated, high-performance solutions.

  • Evaluate and integrate new software and hardware technologies relevant to core Spectrum-X capabilities, including load balancing, telemetry, congestion control and more.

  • Translate product and business requirements into system architecture, component requirements, interfaces, and technical execution plans.

  • Identify architectural gaps, dependencies, tradeoffs, and performance bottlenecks across the end-to-end system.

  • Work closely with productization teams, including test, validation, deployment, and support, to ensure the complete solution is reliable, scalable, and ready for production.

  • Author architecture documents, design specifications, technical requirements, and  technical publications.

  • Provide technical leadership and guidance to engineering teams throughout implementation and integration.

 

What We Need to See:

  • Bachelor’s, Master’s, or PhD degree in Computer Science, Electrical Engineering, or equivalent experience.

  • 5+ years of experience in software architecture, systems engineering, or the development of large-scale, performance-critical systems.

  • Strong networking background, including a deep understanding of high-performance networks, distributed systems, and networked applications.

  • Deep understanding of deep learning systems,  GPU acceleration, and AI model execution flows

  • Proven experience defining and delivering end-to-end architectures that span software, hardware, networking, and infrastructure.

  • Experience leading complex technical initiatives in a large-scale, multi-functional environment.

  • Ability to translate broad product goals into clear architectural requirements, interfaces, tradeoffs, and execution plans.

  • Excellent communication and technical leadership skills, with the ability to influence decisions across teams with multifaceted strengths and organizational boundaries.

 

Ways to Stand Out from the Crowd:

  • Experience architecting high-performance networking solutions for AI, cloud, data center, or distributed computing environments.

  • Familiarity with NVIDIA networking technologies and the Spectrum-X platform.

  • Background in AI training or inference infrastructure, GPU-accelerated systems, or large-scale compute clusters.

  • Experience with AI Accelerators and distributed communication patterns, congestion control and/or load balancing.

  • Proven success identifying and resolving efficiency constraints across complex, multi-component systems.

NVIDIA is widely considered one of the most desirable places to work in technology. We are passionate about what we do and committed to a culture of technical perfection, innovation, and teamwork. If you want to define comprehensive system builds that combine advanced networking, accelerated computing, and large-scale software systems, this role is for you.

How we rate this

Senior Software E2E Architect at NVIDIA rates 80 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

System ArchitectureDistributed SystemsNetworkingDeep learningGPU AccelerationSpectrum XGPUs

Questions you could be asked

  1. Tell me about a project where system architecture was part of your work. What did you do?
  2. Tell me about a project where distributed systems was part of your work. What did you do?
  3. Tell me about a project where networking was part of your work. What did you do?
  4. Tell me about a project where deep learning was part of your work. What did you do?
  5. Tell me about a project where gpu acceleration was part of your work. What did you do?

Adapt your resume

  • List these exact terms on your resume: System Architecture, Distributed Systems, Networking, Deep learning, and GPU Acceleration. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
  • Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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