Senior Product Architect, K8s-Based AI Infrastructure

NVIDIA is hiring a Senior Product Architect, K8s-Based AI Infrastructure in Santa Clara, United States. It pays $184k-$288k a year and Level rates it ; you can apply on NVIDIA.

Level's read on this job

Works on AI ●●●○ is how Level rates this role: the daily work is on AI products, without building the model.
Tools and skills the posting cites include RAG, fine tuning and AI evaluation.
Level classifies it as a senior role.
Level lists 2,700+ other open roles at NVIDIA.

AI in this role

ragfine-tuningai-evaluation

NVIDIA is the engine of modern Artificial Intelligence, Parallel Compute Infrastructure, and Agentic AI - the biggest technology breakthroughs of our time. We’re on a mission to redefine how data moves, connects, and accelerates workloads at scale, and we’re seeking a visionary Product Architect with strong expertise in systems architecture to join our cause. As a key member of our team, you’ll design and shape the architectures that connect the world’s most powerful AI clusters. As a Product Architect at NVIDIA, you'll be the linchpin in transforming ideas into well-defined, functional products, balancing technical feasibility with user needs and market demands. You'll be responsible for designing and overseeing the development of cutting-edge AI solutions from conception through their entire lifecycle. Working at NVIDIA is all about efficiency and multiplying efforts; being a Product Architect is at the nexus of this ethos!

What you’ll be doing:

Stay at the forefront of technology trends in AI Infrastructure & Agentic AI, proposing new product concepts
Define detailed product architectures, including performance, scalability, interoperability, and datacenter deployment requirements
Lead prototyping and testing processes to validate product design and functionality, with a focus on scale, diagnosing bottlenecks and driving innovations in performance
Iterate and refine designs based on feedback, testing results, and evolving requirements
Collaborate with internal hardware, software, security and systems teams to ensure flawless integration of networking, compute and storage ecosystems
Work closely with partners and customers to conceptualize ideal solutions, build proof-of-concepts (POCs) and minimum viable products (MVPs) that demonstrate your vision
Provide comprehensive documentation for product designs, including technical specifications and user guides
Develop targeted content such as whitepapers, blogs, and curriculum for customers, partners, and users

What we need to see:

8+ years of experience architecting datacenter-scale HPC or AI infrastructure as a Principal Architect, Solutions Architect, Principal Engineer, or equivalent
Bachelors degree in computer science or related field (or equivalent experience).
Strong background in technologies that enable large scale infrastructure management of complex systems, networks, and storage
Extensive experience with DevOps solutions, including Python, Ansible, Container Runtimes, Kubernetes, and data center deployments
Familiarity with AI workloads, including agentic & RAG-based workflows, inference at scale, large scale training & fine-tuning, and model evaluation
Exceptional communication skills, with the ability to translate complex technical details for diverse audiences
A passion for staying updated with the latest technological advancements in AI and related fields

Ways to stand out from the crowd:

Prior first-hand experience on having built large scale AI infrastructure
Advanced certifications or publications in AI, deep learning, or related fields
Experience leading high-impact projects or initiatives in cutting-edge tech domains

NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. If you're creative and autonomous, we want to hear from you!

Your base salary will be determined based on your location, experience, and other objective job-related factors. The expected base salary ranges for this position are:
184,000 USD – 287,500 USD for Level 4; and 224,000 USD – 356,500 USD for Level 5.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until November 3, 2026.

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

How we rate this

Senior Product Architect, K8s-Based AI Infrastructure at NVIDIA rates 65 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.

Classification

Works on AI. The daily work is on AI products, without building the model.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ 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.

Key facts

Senior Product Architect, K8s-Based AI Infrastructure is an open job at NVIDIA.
Level rates this role AI Level 3 of 4: Works on AI.
The listed salary is $184k-$288k a year.
The role is based in US, CA, Santa Clara.
The job was posted on August 20, 2026.
Seniority: senior.
Applications are handled by NVIDIA. Apply on NVIDIA

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

RAGFine-tuningAI Evaluation

Questions you could be asked

How would you design a retrieval step so the model answers from real data instead of guessing?
Walk me through fine-tuning a model: what data did you use, and how did you check the result?
How do you decide that one model's output is better than another's for a given task?
Describe a typical day in a role like this one: which parts run through AI directly?
If you removed AI from this role, what would be left, and how do you decide what still needs a human?

Adapt your resume

List these exact terms on your resume: RAG, Fine-tuning, and AI Evaluation. 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.
Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.

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