Senior Software E2E Architect
Nvidia
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What architect roles keep asking for: AWS (32%), Python (25%), Azure (22%), GCP (16%), Stakeholder management (14%), LLMs (13%), Customer success (13%), Generative AI (12%) — counted across their open postings here.
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Interviews for architect roles keep coming back to AWS, Python, Azure, GCP. Practise those questions before you sit with Nvidia.
Questions you are likely to be asked
- Why do you want to join Nvidia?
- What is your experience with Deep learning? Tell me one thing you learned the hard way.
- How would you design an API for a feature you have worked on?
- What do you do when a production issue happens on your code?
- Walk me through a system you built. How was it designed, and what would you change now?
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Practise the Senior Software E2E Architect at Nvidia interview free →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.
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Listed on workday · posted 2026-09-30. ApplySarthi collects openings and links to application pages; the role is advertised by Nvidia, not by us.