Principal Enterprise Data & AI Information Architect

Principal Enterprise Data & AI Information Architect

Xperi invents, develops and delivers technologies that create extraordinary experiences at home and on the go for millions of people around the world. Powering billions of consumer electronics, connected cars and digital content titles, we make entertainment more immersive, driving more intelligent and every interaction seamlessly personalized through our renowned consumer brands:

DTS®, HD Radio™ andTiVo®.

Xperi (NYSE: XPER) is a publicly traded technology company headquartered in San Jose, CA with over 1,500 employees across North America, Europe and Asia. Come join a thriving team where you can play an integral role in shaping the future of entertainment technology.

Xperi is transforming how enterprise technology, data, automation, and AI work together across the company.

Our business operates across a diverse ecosystem of enterprise platforms including Salesforce, Net Suite, Service Now, Atlassian, data platforms, AI services, and custom applications. While these systems successfully support business operations, critical business information is often represented differently across platforms, creating inconsistency, complexity, and barriers to automation.

We are building a modern enterprise data foundation that will power reporting, analytics, automation, copilots, AI agents, and future digital experiences.

The Principal Enterprise Data & AI Information Architect will lead the design of that foundation.

This individual will define how enterprise data is modeled, connected, governed, and understood across the company, creating a scalable semantic architecture that enables trusted business decisions and AI-driven operations.

This is a highly visible Principal-level individual contributor role reporting directly to the CIO and partnering with executive leadership across Finance, Sales, Operations, Product, HR, Legal, and Engineering.

The Principal Enterprise Data & AI Information Architect is responsible for defining the enterprise-wide data architecture strategy and establishing a unified semantic framework across all business platforms.

This role serves as the authoritative leader for enterprise data definitions, canonical business models, semantic architecture, metadata strategy, and AI-ready data structures.

The role does not own data engineering execution, reporting development, or integration delivery. Instead, it establishes the architectural standards that those teams implement.

When multiple systems produce different answers to the same business question, this role owns identifying and eliminating the underlying data architectural cause.

• Define and evolve Xperi’s enterprise data architecture roadmap
• Establish long-term data strategy supporting analytics, automation, AI, and digital transformation initiatives
• Partner with executive stakeholders to identify enterprise information priorities
• Align data architecture with business and technology strategy
• Define and maintain enterprise canonical data models
• Customer
• Account
• Product
• Revenue
• Contract
• Subscription
• Employee
• Asset
• Operational Metrics
• Drive adoption of standardized business definitions across enterprise platforms
• Eliminate duplicate and conflicting representations of business information

• Design and establish the enterprise semantic layer
• Create shared business vocabulary and metric definitions
• Define enterprise business ontology and relationships between key data domains
• Enable consistent interpretation of business information across systems
• Establish semantic standards supporting reporting, APIs, automation, and AI applications

• Architect enterprise data structures optimized for:
• Agentic AI platforms
• MCP-enabled architectures
• Knowledge retrieval
• AI orchestration platforms
• Partner with AI teams to ensure trusted and explainable AI outcomes
• Establish frameworks for contextual enterprise knowledge used by AI agents
• Enable future knowledge graph and enterprise memory capabilities

• Standardize data consumption patterns across applications and business functions
• Establish enterprise data contracts and ownership models
• Reduce duplication of business logic across systems
• Data modeling
• Metadata management
• Semantic definitions
• Partner with Security, Compliance, Governance, and Enterprise Application teams

• Influence application, integration, reporting, AI, and engineering teams
• Resolve conflicts across organizations where competing definitions exist
• Serve as trusted advisor to senior leadership on enterprise data strategy

Success in this role will be measured through:

• Adoption of enterprise semantic architecture
• Reduction in conflicting reports and metrics
• Increased reuse of enterprise data assets
• Simplified integration architecture
• Faster delivery of analytics and reporting solutions
• Increased AI effectiveness and trustworthiness
• Reduced time spent…