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 other objective job-related factors. The expected base salary ranges for this position are:
- 168,000 USD – 270,250 USD for Level 4; and 200,000 USD – 322,000 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.