Drimva

NVIDIA

Software Engineer, Technical Lead – Performance Data Platform

$272K–$431K

US, CA, Santa Clara · Full-time · Posted Oct 29, 2026

Experience
15+ years of software engineering experience.
Education
Bachelor’s degree in Computer Science, Computer Engineering, or a related field, or equivalent experience.

About the job

Lead the architecture and hands-on development of a data-center-scale platform that stores searchable performance history and helps engineers and automated agents diagnose AI workload performance issues.

What you'll do

  • Define the platform’s architecture, data model, APIs, and integration boundaries; document and align foundational decisions with partner teams.
  • Build early services, APIs, and deployment tooling, then evolve the prototype into a product used by other teams.
  • Guide automated analysis agent behavior, review performance diagnoses, drive early use cases, and mentor engineers.

What they ask for

  • 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 an end-to-end data-intensive platform used by other teams.
  • Experience with systems where automated agents or models process large amounts of production data, including assessing result quality.
  • Practical knowledge of GPU and machine learning workload performance; track record with evolving APIs and data models; proficiency with C++, Go, Python.

Nice to have

  • Background in developer tools, profilers, or performance-analysis products; experience turning a prototype into a multi-team platform.
  • Experience with identity, access control, and multi-tenant products; agent/model evaluation methods; working knowledge of SQL and TypeScript.

Pay

272,000 USD - 431,250 USD (base salary)

Tools

C++, Go, Python, SQL, TypeScript

AI focus

Build a platform where automated analysis agents find and explain performance issues in AI workloads; define their permitted queries, evidence relationships, and cost and response-time constraints. Experience with AI tools in recruiting is also stated.

Model-written summary · the original posting is authoritative

First seen Oct 30, 2026 · Last verified Nov 4, 2026 (UTC)