Open Source Platform Architect
NVIDIA is hiring an Open Source Platform Architect in Santa Clara, United States. It pays $168k-$270k a year and Level rates it ; you can apply on NVIDIA.
Level's read on this job
- Level rates this role Works on AI ●●●○: the daily work is on AI products, without building the model.
- Tools and skills the posting cites include Claude, Copilot and Cursor.
- Level classifies it as a senior role.
- Level lists 2,700+ other open roles at NVIDIA.
AI in this role
Lead and evolve the internal open-source platform and infrastructure that scores and tracks AI readiness across projects.
For more than 25 years, NVIDIA has driven innovation in computer graphics, PC gaming, and accelerated computing. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re harnessing the boundless possibilities of AI to build the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world.
DSX OS is NVIDIA's open source foundation for AI infrastructure. It is a growing portfolio of engineering teams building in the open. Every project in that portfolio needs to meet a shared bar for open-source readiness: code hygiene, governance, community health. Today, that's measured by hand, project by project. This role owns an internal product that changes that to a platform that scores, tracks, and reports on readiness across the DSX OS portfolio, and the roadmap that takes it from an internal utility to the definition of what "open source ready" means for DSX OS.
What you'll be doing:
Lead the platform as production infrastructure. Maintain, harden, and evolve it from a measurement tool into the system every DSX OS project runs on — reliability and data quality matter because everything else in the program depends on it.
Automate scoring. Replace manual review-fix-recheck loops with tooling, so the portfolio scales through automation instead of added effort. Self-serve integration.
Build scoring into onboarding and workshop experiences. This lets participants get real-time feedback on their own project instead of waiting for manual review. It increases how many teams a single event can support.
Engineering team feedback loop. Work directly with the project teams using the platform, capture friction signals, and feed them back into the product instead of letting issues pile up in a backlog.
Readiness tracking and reporting. Automate the generation and tracking of per-project readiness plans so status, blockers, and progress are transparent to leadership without manual assembly.
What we need to see:
8+ years of relevant experience and a bachelors degree (or equivalent experience)
Experience leading a software product or internal platform end-to-end and making the calls on what gets built, why, and in what order
Strong software engineering skills, with a track record of turning manual, error-prone processes into reliable automation
Hands-on experience with agentic coding tools (e.g., Claude Code, Copilot, Cursor) as part of your actual engineering workflow, not just casual use
Experience running a production system in the real world — on-call, incident response, or otherwise owning uptime and reliability for something people depend on daily
Experience building reporting or dashboards that a non-engineering audience (leadership, partners) can trust as a source of truth
Ownership mentality for production systems — system dependability and integrity of data fall under your responsibility, not someone else 's
Ways to stand out from the crowd:
Built or operated a rubric-based scoring or compliance system — quality gates, readiness checks, policy-as-code — where the output has to be defensible enough for people to act on it
Experience using LLMs within an evaluation pipeline (LLM-as-judge, qualitative signal assessment at scale) rather than only deterministic pass/fail checks
Designed a metric or signal taxonomy from scratch — deciding what to measure, how to weight it, and how to keep a single score relevant as the system it measures evolves
Built a tool that abstracts over multiple backends or platforms (e.g., supporting both GitHub and GitLab) so it isn't locked to one provider's API
Experience with GitOps-style automation — automated checks that run against every repo or PR or equivalent experience without a human in the loop
Widely considered to be one of the technology world’s most desirable employers, NVIDIA offers highly competitive salaries and a comprehensive benefits package. As you consider your future, explore what we can provide for you and your family at www.nvidiabenefits.com/
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 168,000 USD - 270,250 USD.You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until October 12, 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
Open Source Platform Architect 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.
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.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Questions you could be asked
- Tell me about a project where platform engineering was part of your work. What did you do?
- Tell me about a project where open source was part of your work. What did you do?
- Tell me about a project where automation was part of your work. What did you do?
- Tell me about a project where infrastructure was part of your work. What did you do?
- Walk me through how you've used Claude in your day-to-day work.
Adapt your resume
- List these exact terms on your resume: Platform Engineering, Open Source, Automation, Infrastructure, and Claude. 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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