Make foundational decisions and justify them in documents. Include considered alternatives and evidence that could reverse them. Align these decisions with partner teams and their roadmaps.
Build in the early phase: stand up services, APIs and a deployment path yourself, so that partners can develop the system before every role is filled.
Explain how automated analysis agents operate within the platform. Describe what queries they may perform, how their results relate to evidence, and the constraints on their cost and response time.
Review performance diagnoses and drive the first use cases with design partners, mentor engineers, and establish the engineering approaches the team grows into.
What we need to see
Bachelor’s degree in Computer Science, Computer Engineering, or a related field, or equivalent experience.
15+ years of software engineering experience, including technical leadership of a data-intensive platform that shipped end to end and was used by other teams.
Experience developing or managing systems where automated agents or models process large amounts of production data, including methods used to assess the quality of their results.
Practical knowledge of GPU and machine learning workload performance: you can review a performance diagnosis, question its evidence, and decide which signals matter most.
A track record of crafting APIs and data models that evolved without breaking existing users or deployments.
Hands-on ability to build and deploy services and tooling yourself, including when using automated development tools, and to verify the result independently through tests and measurements.
Clear communication of build choices, trade-offs and uncertainty to engineers, partner teams and leadership, and the ability to align teams without direct authority.
Proficiency with C++, Go, Python.
Ways to stand out from the crowd
Background in developer tools, profilers or performance-analysis products.
Experience transforming a prototype into a platform embraced by multiple teams with distinct priorities.
Identity, access control and multi-tenant build for products that hold customers’ data.
Evaluation approach for the output of analysis agents or models: labeled cases, precision and recall, abstention.
Working knowledge of SQL and TypeScript.
Join NVIDIA and be part of a team that’s redefining what’s possible through technology. Together, we’ll build a platform that sets new standards for performance data analysis and empowers engineers worldwide to achieve flawless results!
Your base salary will be determined based on your location, experience, and other objective job-related factors. The expected base salary range for this position is 272,000 USD – 431,250 USD.
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.
