Principal Enterprise Data & AI Information Architect

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, NetSuite, ServiceNow, 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.

Role Overview 

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.

Key Responsibilities 

Enterprise Data Strategy

• 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

Enterprise Data Modeling 

• Define and maintain enterprise canonical data models
• Establish common business entities including:
• Customer
• Account
• Product
• Revenue
• Contract
• Subscription
• Pipeline
• Employee
• Asset
• Operational Metrics
• Drive adoption of standardized business definitions across enterprise platforms
• Eliminate duplicate and conflicting representations of business information

Semantic Architecture & Business Ontology 

• 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

AI & Agentic Data Enablement 

• Architect enterprise data structures optimized for:
• Microsoft Copilot
• Agentic AI platforms
• MCP-enabled architectures
• Enterprise search
• 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

Data Products & Enterprise Consumption 

• Define reusable enterprise data products
• Standardize data consumption patterns across applications and business functions
• Establish enterprise data contracts and ownership models
• Reduce duplication of business logic across systems

Architecture Governance 

• Es