Product Engineer, Developer Platform

NVIDIA is a technology company advancing computer graphics, gaming, accelerated computing, and AI infrastructure. The Product Engineer will own and evolve an internal platform for measuring, tracking, and reporting open-source readiness across the DSX OS portfolio, while automating scoring, onboarding feedback, and readiness reporting.

Responsibilities:

• 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

Requirements:

• 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
• 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