Principal Networking AI Systems Architect
Nvidia
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This role on the market
383 open networking roles across 52 companies are on ApplySarthi right now, most of them in Bengaluru (29), Chennai (6), Pune (1).
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What networking roles keep asking for: Python (33%), Linux (30%), C++ (25%), System design (19%), AWS (18%), Kubernetes (14%), Java (12%) — counted across their open postings here.
Nvidia has 3,820 open roles listed here.
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Counted across 14 company job boards, updated as roles open and close.
Preparing for this interview
Interviews for networking roles keep coming back to Python, Linux, C++, System design. 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 LLMs? Tell me one thing you learned the hard way.
- When would you not use machine learning for a problem?
- Walk me through a model you built, from the data to how it was used.
- How did you know your model was actually good, and not just good on your test set?
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Practise the Principal Networking AI Systems Architect at Nvidia interview free →We are seeking a highly skilled Principal Networking AI System Architect to join as a key contributor to the Applied Networking AI group. In this role you will scope and lead AI based solutions for networking technologies and drive their integration across teams.You’ll lead a portfolio and roadmap of projects that encompass agentic-AI for data-center management, predictive-resiliency, optimization and more. By collaborating closely with subject-matter-experts (SMEs), applied-researchers, product-managers, architects, data-engineers and other stakeholders you will push the envelope forward in using cutting-edge technologies and data-driven insights to improve NVIDIA's products. What you'll be doing: Build a shared roadmap and vision for AI based data-center management solutions spanning LLM intelligence for troubleshooting, predictive-resiliency and AIOPS, black-box optimization and performance tuning. Work closely with engineering and reliability teams to scope and define workflows utilizing and benefitting from AI/ML. Drive the integration of AI capabilities into system architecture and engineering workflows. Identify system-level opportunities for failure management, automated troubleshooting, performance improvement, and resource optimization. Translate system behavior, dependencies, data, and operational constraints into formulated research problems. What we need to see: Ph.D in electrical engineering, machine-learning, computer-science or another relevant field. 10+ years of deep technical experience in high-performance network architecture, data center networking, or distributed systems design. Mastery of high-speed interconnect protocols including InfiniBand and/or advanced Ethernet architectures. Thorough experience driving high-impact projects centered on modern AI/ML such as LLMs/agents, deep-learning, black-box optimization or another relevant field. Deep knowledge of AI/ML and networking-hardware/system-architecture. Excellent ability to convey and communicate data-based insights to stakeholders and management. Experience demonstrating an excellent track of collaboration with hands-on teams. Ways to stand out from the crowd: Demonstrated track record of architecting and deploying multi-thousand-node GPU clusters for hyperscale cloud environments. Deep knowledge of NVIDIA networking technologies, including BlueField DPUs, Quantum InfiniBand switches, and Spectrum Ethernet platforms. Expertise in in-network computing, telemetry, adaptive routing, and telemetry-driven network optimization. High energy and a positive, proactive and curious approach.
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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.