Principal Engineer - Enterprise Content and AI Data Platform

at Nvidia

USD 248,000-391,000 per year

SENIOR

✅ On-site

Tech Stack
Tag name is followed by "@" symbol and proficiency level value. About proficiency levels:

1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;

3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;

7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;

10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.

AI @ 4 API @ 6 Audit @ 3 Communication @ 6 Compliance @ 3 Data Pipelines @ 4 Databricks @ 4 Distributed Systems @ 7 Engineering Management HPC LLM @ 4 Leadership @ 4 Mentoring @ 4 RAG @ 4 Security @ 3 Slack @ 6

Details

NVIDIA is hiring a Principal Engineer to lead three interconnected platform charters at the intersection of information security, enterprise collaboration, and AI. These platforms protect sensitive content, govern enterprise data access, and power AI agents at scale, with a focus on access-control fidelity, export-control enforcement, and production readiness. This is a high-impact individual contributor role with a path toward engineering leadership and management.

Responsibilities

Sensitive Information Protection and Remediation

Own the roadmap for sensitive-information detection and remediation.
Partner with Finance, Legal, and Security to define classification models, remediation workflows, and trusted reporting.
Lead build-versus-buy decisions and vendor evaluations for third-party DLP or search tools.

Enterprise Data Access and Governance

Drive production rollout and self-service onboarding for an enterprise data access platform.
Work with connectors across Outlook, Teams, Slack, Confluence, OneDrive, SharePoint, Google Drive, and 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

Integrate enterprise content sources, including document stores, wikis, and cloud drives, into the AI knowledge platform.
Ensure content is accurate, fresh, and access-controlled for AI-agent consumption.
Define production-readiness gates and maintain a clear ownership boundary focused on integration correctness and quality rather than full platform operations.

Leadership and Cross-Functional Coordination

Serve as the technical lead across all three workstreams.
Align stakeholders across Security, Finance, Legal, and AI platform teams while driving clarity on ownership and priorities.
Mentor engineers and foster documentation, runbooks, and operational rigor.
Demonstrate readiness to grow into an engineering management role.

Requirements

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 increasing 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, such as Confluence, SharePoint, Google Drive, Slack, or Teams.
Ability to drive cross-functional alignment across Security, Legal, Finance, and platform engineering teams.
Excellent written and verbal communication skills, including the ability to translate complex technical tradeoffs into executive-level clarity.
Experience mentoring peers, leading projects, or taking on informal leadership responsibilities.
Comfort working through ambiguity and driving decisions in a fast-paced, high-stakes environment.

Preferred Qualifications

Experience with AI/LLM data pipelines, vector stores, or RAG architectures, particularly 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 and DLP products and their integration patterns.
Experience with vendor evaluation and build-versus-buy decisions for enterprise security or content platforms.
Ability to use AI and agentic automation to improve operational efficiency and reduce engineering toil.
Track record of leading platform migrations, tenant consolidations, or governance modernization efforts.

Benefits

Base salary range of $248,000-$391,000 USD, determined by location, experience, and compensation for similar positions.
Eligibility for equity and benefits.
NVIDIA is an equal opportunity employer committed to an inclusive work environment.
NVIDIA uses AI tools in its recruiting processes.

Applications will be accepted at least until July 28, 2026. This posting is for an existing vacancy.