NVIDIA is hiring a Principal Engineer to lead three interconnected and strategic platform charters at the intersection of information security, enterprise collaboration, and AI - forming the backbone of how NVIDIA protects sensitive content, governs enterprise data access, and powers the next generation of AI agents at scale. These platforms span sensitive-information protection and DLP, a central data governance layer that controls access to enterprise content across email, messaging, document stores, and search, and an enterprise AI knowledge platform that ingests and validates content for reliable consumption by AI agents - with a consistent focus on access control fidelity, export-control enforcement, and production readiness. This is a high-impact individual contributor role with a clear path into engineering leadership and management. We are looking for a technically strong engineer who is eager to grow beyond IC execution - someone who can own platform strategy, influence cross-functional stakeholders, and eventually step into leading and growing a team. Strong cross-functional partnership across Security, Legal, Finance, and AI platform teams is essential from day one.
What You Will Be Doing:Sensitive Information Protection & Remediation
- Own the roadmap for sensitive-information detection and remediation - partnering with Finance, Legal, and Security to define classification models, remediation workflows, and reporting that leadership can trust.
- Lead build-vs-buy decisions and vendor evaluations to determine what to invest in internally versus augment with third-party DLP or search tools.
Enterprise Data Access & Governance
- Drive production rollout and self-service onboarding for the enterprise data access platform, spanning connectors across email, messaging, document stores, and search (Outlook, Teams, Slack, Confluence, OneDrive, SharePoint, Google Drive, Glean).
- Design and implement export-control enforcement and long-term audit logging - including authorization checks, schema design, data masking, retention, and RBAC controls. Evaluate third-party partners that could extend the platform for NVIDIA's customer-facing go-to-market motions.
Enterprise AI Knowledge Platform
- Drive integration of enterprise content sources - document stores, wikis, and cloud drives - into the AI knowledge platform, ensuring content is accurate, fresh, and access-controlled for agent consumption.
- Define production readiness gates and maintain a clear ownership boundary: this team owns integration correctness and quality, not full platform operations.
Leadership & Cross-functional Coordination
- Serve as the technical lead across all three workstreams, aligning stakeholders in Security, Finance, Legal, and AI platform teams and driving clarity on ownership and priorities.
- Mentor engineers and foster a culture of documentation, runbooks, and operational rigor; demonstrate readiness to grow into an engineering management role.
What We Need To See:- Bachelor's or Master's Degree in Computer Science, Computer Engineering, or a related field (or equivalent experience).
- 15+ years of experience building and operating large-scale enterprise platforms, with a track record of growing technical scope and influence beyond individual execution.
- Strong foundation in backend systems, distributed systems, and high-performance computing - experience with large-scale data processing, indexing pipelines, and systems designed for reliability and scale.
- Background in enterprise security, data governance, or compliance platforms - familiarity with classification, remediation workflows, access control models, and audit requirements is a plus.
- Experience building or integrating secure API platforms, data connectors, or enterprise SaaS integrations at scale (e.g., Confluence, SharePoint, Google Drive, Slack, Teams, or similar).
- Proven ability to drive cross-functional alignment across Security, Legal, Finance, and platform engineering teams.
- Excellent written and verbal communication skills; ability to translate complex technical tradeoffs into executive-level clarity.
- Demonstrated interest in growing into engineering leadership - experience mentoring peers, leading projects, or taking on informal leadership responsibilities is a strong signal.
- Comfortable holding ambiguity and driving decisions in a fast-paced, high-stakes environment.
Ways to Stand Out From The Crowd:- Experience with AI/LLM data pipelines, vector stores, or RAG architectures - particularly in connecting enterprise content sources to AI platforms with strict access controls.
- Hands-on experience with Databricks or similar platforms for audit logging, data governance, and RBAC. Familiarity with Glean or similar enterprise search/DLP products and their integration patterns.
- Experience with vendor evaluation and build-vs-buy decisions for enterprise security or content platforms.
- Ability to leverage AI and agentic automation to drive operational efficiency and reduce engineering toil.
- Track record of leading platform migrations, tenant consolidations, or governance modernization efforts.
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 248,000 USD - 391,000 USD.
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until July 28, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
