1 day ago
Base Salary
$168k - $322k/yr
Responsibilities
- Own the roadmap for sensitive-information detection, classification, remediation workflows, and leadership reporting.
- Drive production rollout and self-service onboarding for enterprise data access connectors across collaboration, document, and search systems.
- Design export-control enforcement, audit logging, authorization checks, data masking, retention, and RBAC controls.
- Integrate enterprise content sources into the AI knowledge platform and enforce freshness, accuracy, and access-control quality standards.
- Serve as technical lead across the platform charters, make architectural decisions, resolve ambiguity, and mentor engineers through code and design reviews.
Requirements
- Bachelor's or Master's degree in Computer Science, Computer Engineering, or a related field, or equivalent experience.
- 8+ years of experience building and operating large-scale enterprise platforms with increasing technical scope and ownership.
- Strong foundation in backend systems, distributed systems, data engineering, large-scale data processing, indexing pipelines, reliability, and scale.
- Experience building or integrating data connectors or enterprise SaaS integrations.
- Experience training and evaluating ML models for classification, especially for security, content sensitivity, or information governance.
- Strong communication skills and the ability to explain technical tradeoffs to non-technical stakeholders.
- Ability to make decisions with incomplete information and adapt as priorities change.
- Familiarity with access-control models, remediation workflows, audit requirements, AI/LLM data pipelines, vector stores, or RAG architectures is preferred.
- Hands-on Databricks experience for audit logging and RBAC, familiarity with Glean or similar enterprise search/DLP products, and experience leading migrations or governance modernization are preferred.
- Experience mentoring engineers or leading cross-functional projects involving Security, Legal, Finance, and platform teams is preferred.
Benefits
- Eligible for equity and benefits.
- Applications will be accepted at least until September 8, 2026.
- The posting is for an existing vacancy.
Tech Stack
Databricks
Categories
BackendData Engineering
About Nvidia
Since its founding in 1993, NVIDIA (NASDAQ: NVDA) has been a pioneer in accelerated computing. The company’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined computer graphics, ignited the era of modern AI and is fueling the creation of the metaverse. NVIDIA is now a full-stack computing company with data-center-scale offerings that are reshaping industry.