N

NVIDIA

Designs the chips and software that power AI

Open Source Platform Architect

Technical Product ManagementConfirmed live in the last 24 hours
Full-timeRemote

About the Job

Requirements

  • At least 8 years of relevant experience and a bachelor's degree or equivalent experience.
  • Experience leading a software product or internal platform end-to-end and making decisions about what gets built, why, and in what order.
  • Strong software engineering skills and a track record of turning manual, error-prone processes into reliable automation.
  • Hands-on experience with agentic coding tools such as Claude Code, Copilot, or Cursor as part of an engineering workflow.
  • Experience running a production system, including on-call, incident response, or otherwise owning uptime and reliability for a system people depend on daily.
  • Experience building reporting or dashboards that a non-engineering audience, such as leadership or partners, can trust as a source of truth.
  • Ownership mentality for production systems, with responsibility for system dependability and data integrity.

Responsibilities

  • Lead the platform as production infrastructure by maintaining, hardening, and evolving it from a measurement tool into the system every DSX OS project runs on, ensuring reliability and data quality.
  • Automate scoring by replacing manual review-fix-recheck loops with tooling and enabling self-service integration.
  • Build scoring into onboarding and workshop experiences so participants receive real-time feedback on their own projects and a single event can support more teams.
  • Work directly with project teams using the platform, capture friction signals, and feed them back into the product.
  • Automate the generation and tracking of per-project readiness plans so status, blockers, and progress are transparent to leadership without manual assembly.

Desired Qualifications

  • Built or operated a rubric-based scoring or compliance system, such as quality gates, readiness checks, or policy-as-code, with defensible outputs people can act on.
  • Experience using large language models within an evaluation pipeline, such as LLM-as-judge or 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 measured system evolves.
  • Built a tool that abstracts over multiple backends or platforms, such as supporting both GitHub and GitLab, rather than depending on one provider's API.
  • Experience with GitOps-style automation, including checks that run against every repository or pull request without a human in the loop, or equivalent experience.

About the Company

NVIDIA

Designs the chips and software that power AI

NVIDIA designs the chips and software that power artificial intelligence and sells complete data center systems to cloud providers, AI labs, and other businesses, along with GeForce graphics cards for gamers. Its GPUs, chips that perform thousands of calculations at once, became the main hardware for AI after researchers used them to train the AlexNet image-recognition model in 2012. NVIDIA connects many GPUs with its own processors and networking gear into servers and rack-sized computers, and developers program them through its CUDA software. These systems bring in most of its sales, and it also makes chips for cars and robots. Jensen Huang co-founded NVIDIA in 1993, and it is based in Santa Clara, California.

Company size
10,001+
Company stage
IPO
Headquarters
Santa Clara, CA
Founded
1993

Recently Posted Jobs

Explore more opportunities at NVIDIA

See more jobs