Principal Engineer - Enterprise Content and AI Data Platform
$248,000–$391,000 year
On-siteSanta Clara, California, United States
Job Summary
Own the roadmap for sensitive-information detection and remediation, partnering with Finance, Legal, and Security to define classification models and vendor evaluations for DLP tools. Drive production rollout of the enterprise data access platform across email, messaging, and document stores, while designing export-control enforcement, audit logging, and RBAC controls. Integrate enterprise content sources into the AI knowledge platform to ensure accuracy and access fidelity for agent consumption. Serve as technical lead across all three workstreams, aligning stakeholders and mentoring engineers to foster operational rigor. This high-impact individual contributor role offers a clear path into engineering leadership with strong cross-functional coordination across Security, Legal, Finance, and AI teams.
Required Qualifications
- 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
- Strong foundation in backend systems, distributed systems, and high-performance computing
- experience with large-scale data processing
- experience with indexing pipelines
- systems designed for reliability and scale
- 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
- taking on informal leadership responsibilities
- Comfortable holding ambiguity
- driving decisions in a fast-paced, high-stakes environment
Desired Qualifications
- Background in enterprise security, data governance, or compliance platforms
- familiarity with classification
- familiarity with remediation workflows
- familiarity with access control models
- familiarity with audit requirements
- Experience building or integrating secure API platforms
- data connectors
- enterprise SaaS integrations at scale
- Experience with Confluence
- SharePoint
- Google Drive
- Slack
- Teams
- or similar
- Experience with AI/LLM data pipelines
- vector stores
- RAG architectures
- connecting enterprise content sources to AI platforms with strict access controls
- Hands-on experience with Databricks
- similar platforms for audit logging
- data governance
- RBAC
- Familiarity with Glean
- similar enterprise search/DLP products
- their integration patterns
- Experience with vendor evaluation
- build-vs-buy decisions for enterprise security or content platforms
- Ability to leverage AI and agentic automation
- drive operational efficiency
- reduce engineering toil
- Track record of leading platform migrations
- tenant consolidations
- governance modernization efforts
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