Senior Enterprise Data & AI Semantic Architect

Xperi Inc.

San Jose (CA)

On-site

USD 158,000 - 209,000

Full time

14 days+

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Benefits offered by this job

Competitive compensation
Generous time off
Hybrid work environment

Job summary

Xperi Inc. in San Jose, CA is seeking a Principal Enterprise Data & AI Information Architect to define the enterprise-wide data architecture strategy and establish a unified semantic framework across business platforms.

You will lead canonical data models, semantic standards, and AI-ready data structures, partnering with executives to enable trusted decisions, analytics, and AI applications without owning ETL or reporting development.

Qualifications

  • 12+ years in Enterprise Data Architecture, Information Architecture, or Data Platform Leadership.
  • Deep expertise in semantic layers, metadata management, and API-centric architectures.
  • Experience across complex SaaS ecosystems and modern cloud data architectures.
  • Proven ability to guide AI, machine learning, copilots, or agentic AI initiatives.

Responsibilities

  • Define and evolve the enterprise data architecture roadmap aligned to analytics, AI, and digital transformation.
  • Establish the enterprise semantic layer and shared vocabulary for consistent interpretation.
  • Lead data contracts, ownership models, and metadata standards across platforms.
  • Partner with executive stakeholders to set information priorities and governance.
  • Influence engineering, integration, reporting, and AI teams without direct authority.

Skills

Semantic layers
Metadata management
API-centric architectures
SaaS ecosystem knowledge
Cloud data architectures
Executive communication
AI governance

Tools

Salesforce
NetSuite
ServiceNow
Atlassian
Microsoft Azure
Databricks
Snowflake

Job description

Xperi Inc. in San Jose, CA is seeking a Principal Enterprise Data & AI Information Architect to define the enterprise-wide data architecture strategy and establish a unified semantic framework across business platforms.

You will lead canonical data models, semantic standards, and AI-ready data structures, partnering with executives to enable trusted decisions, analytics, and AI applications without owning ETL or reporting development.

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