Senior Engineer, Enterprise Data Governance & AI Trust

NVIDIA Gruppe; Santa Clara (CA); On-site; USD 168,000 - 322,000; Full time

Benefits offered by this job

Equity

Benefits

Job summary

NVIDIA is seeking a Senior Engineer to build its Enterprise Data Governance platform. You will own architecture across sensitive-information protection, governed data access, and knowledge readiness for enterprise AI at scale.

You will lead RBAC, integration with Confluence/SharePoint/Drive-like systems, and drive ML classification improvements while mentoring the team and guiding deployments. Equity and benefits accompany the base salary, with applications open until the date stated in the ad.

Qualifications

• Bachelor's or Master's Degree in Computer Science, Computer Engineering, or related field (or equivalent experience).
• 8+ years building and operating large-scale enterprise platforms with ownership.

Responsibilities

• Own roadmap for sensitive-information detection, remediation, and reporting for leadership trust.
• Evaluate ML-based classification for sensitive content at scale with precision/recall balance.
• Drive production rollout and self-service onboarding for enterprise data access across email, messaging, and document stores.
• Design export-control enforcement, audit logging, and RBAC across connected systems.
• Integrate enterprise content sources into AI knowledge platform ensuring correct access scope.
• Set and enforce content ingestion quality across integrations from freshness to access-control accuracy.
• Provide technical leadership across all three charters, shape architecture, and mentor engineers.
• Lead code/design reviews and raise engineering standards.

Skills

Backend systems

Distributed systems

Data engineering

ML model training

Communication

Education

Bachelor's or Master's in CS/CE

Tools

Databricks

RBAC

Job description

NVIDIA is seeking a Senior Engineer to build its Enterprise Data Governance platform. You will own architecture across sensitive-information protection, governed data access, and knowledge readiness for enterprise AI at scale.

You will lead RBAC, integration with Confluence/SharePoint/Drive-like systems, and drive ML classification improvements while mentoring the team and guiding deployments. Equity and benefits accompany the base salary, with applications open until the date stated in the ad.