ApplySarthi

Principal Networking AI Systems Architect

Nvidia

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383 open networking roles across 52 companies are on ApplySarthi right now, most of them in Bengaluru (29), Chennai (6), Pune (1).

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.

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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

  1. Why do you want to join Nvidia?
  2. What is your experience with LLMs? Tell me one thing you learned the hard way.
  3. When would you not use machine learning for a problem?
  4. Walk me through a model you built, from the data to how it was used.
  5. 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.