7 days ago
Base Salary
$168k - $322k/yr
Responsibilities
- Own the roadmap for sensitive-information detection, classification, remediation workflows, and trusted reporting.
- Drive production rollout and self-service onboarding for enterprise data access connectors across collaboration, document, and search systems.
- Design export-control enforcement, authorization checks, audit logging, schema design, data masking, retention, and RBAC controls.
- Integrate enterprise content sources into the AI knowledge platform and enforce ingestion quality, freshness, accuracy, and access-control correctness.
- Serve as technical lead, make architectural decisions, resolve ambiguity, conduct reviews, and mentor engineers.
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 such as Confluence, SharePoint, Google Drive, Slack, or Teams.
- Experience training and evaluating ML models for classification, especially in security, content sensitivity, or information governance.
- Strong communication skills and the ability to explain technical tradeoffs to non-technical stakeholders.
- Familiarity with access-control models, remediation workflows, audit requirements, AI/LLM data pipelines, vector stores, or RAG architectures is preferred.
- Hands-on Databricks experience, 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.
- Base salary range is $168,000-$270,250 for Level 4 and $200,000-$322,000 for Level 5, depending on location, experience, and comparable employee pay.
- Applications will be accepted at least until October 19, 2026.
- This posting is for an existing vacancy.
Tech Stack
Databricks
Categories
About Nvidia
Nvidia designs and sells GPUs and accelerated computing platforms for data centers, AI/ML, graphics, gaming, and automotive, monetizing through hardware, software platforms (CUDA, AI frameworks), and systems like DGX and networking. Customers include cloud providers, enterprises, researchers, and OEMs. Founded in 1993 and headquartered in Santa Clara, it is a public company traded on NASDAQ under NVDA.