Senior Manager, AI Lead – Semantic Layer

AAA

Sr. Manager, AI Lead overseeing semantic data product strategies for CSAA Insurance Group.

Posted 5/26/2026full-timeRemote • Alabama, Arizona, California, Colorado, Connecticut, District of Columbia, Florida, Idaho, Illinois, Iowa, Kansas, Kentucky, Louisiana, Maine, Maryland, Massachusetts, Minnesota, Mississippi, Missouri, Montana, South Carolina, Virginia, Washington • 🇺🇸 United StatesSenior💰 $168,300 - $224,300 per yearWebsite

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

product managementdata platform productsontologiessemantic data modelsknowledge graphsdata integrationdata ecosystemsAI/MLanalyticsdata-driven products

Soft Skills

leadershipstrategic thinkingcommunicationcollaborationuser advocacyproblem-solvingadaptabilitymentoringstakeholder engagementproduct ownership

Tools & Technologies

enterprise data systemsdata governance toolsdata quality toolsanalytics platformsAI platformsdata integration toolssemantic layer technologiesdata modeling toolsproject management softwarecollaboration tools

Certifications & Qualifications

Bachelor's degree in Computer ScienceBachelor's degree in EngineeringBachelor's degree in BusinessBachelor's degree in Data Scienceadvanced degree preferred

Industry Keywords

insurancefinancial servicesregulated industrydata standardizationbusiness domainsdata connectivityuser needsoperational outcomesbusiness valuedata quality expectations

About the role

Key responsibilities & impact

Define and drive the vision, strategy, and roadmap for enterprise semantic data and data connectivity across business domains
Partner with business and IT leaders to identify high-value opportunities to connect and standardize data across systems
Position the semantic data product as a product, not just a technical asset, with clear customers, outcomes, adoption goals, and success metrics
Define and evolve the product’s value proposition, ensuring alignment to business priorities and measurable outcomes
Act as the general manager of the product, balancing user needs, technical feasibility, strategic priorities, operational constraints, and business impact
Define and manage data products aligned to key business domains, including clear ownership, users, and success metrics
Define target users and use cases for data products, ensuring alignment to specific decisions, workflows, and business outcomes
Partner closely with business customers to ensure data products support critical decisions, workflows, and operational outcomes
Drive adoption and usage of shared data assets across business units
Identify and prioritize use cases where connected data unlocks measurable business value (e.g., improved decisioning, automation, personalization)
Ensure solutions are aligned to real-world workflows and deliver tangible outcomes
Lead the development and evolution of enterprise ontologies, taxonomies, and data models that represent key business concepts and relationships
Establish a scalable semantic layer that enables reuse across analytics, AI, and operational use cases
Ensure alignment of definitions across domains to reduce fragmentation and duplication
Support both structured and unstructured data integration, enabling downstream AI and analytics applications
Ensure data is discoverable, understandable, and usable across teams through consistent definitions and relationships
Partner deeply with business domains to understand workflows, decision points, and data dependencies, acting as a product owner for how data supports those functions
Own the end-to-end product lifecycle from discovery and definition to delivery and iteration
Define product requirements, success metrics, and release plans
Continuously refine the semantic data product based on user feedback and evolving business needs
Define critical metrics to measure adoption, usability, and impact of the semantic data product
Supervise usage and continuously improve accessibility and value delivery
Evangelize the value of connected semantic data across the organization
Partner with data governance teams to establish standards, definitions, and data quality expectations
Promote consistency, reusability, and scalability of data assets across the enterprise

Requirements

What you’ll need

Bachelor’s degree in Computer Science, Engineering, Business, Data Science, or a related field; advanced degree preferred
10 + years of experience in product management, including experience delivering data or data platform products
Demonstrable ability to lead others directly or indirectly, as demonstrated through 3+ years of leading teams, enterprise-wide programs, or large multi-functional programs
Consistent track record of owning products end-to-end, including strategy, roadmap, delivery, and performance measurement, ideally in insurance, financial services, or another regulated industry
Direct experience developing or working with ontologies, semantic data models, or knowledge graphs, or defining and standardizing business entities and relationships across domains in an enterprise environment
Hands-on experience with enterprise data systems, data platforms, or data integration initiatives
Demonstrated ability to translate business concepts into structured data models and deliver data-driven products or platforms in partnership with technical teams
Strong understanding of data ecosystems, including how data is defined, governed, and connected across domains
Experience enabling AI/ML or analytics use cases through well-structured and connected data
Experience leading or mentoring product managers or cross-functional teams preferred

Benefits

Comp & perks

total compensation package
annual bonus eligibility for most roles
401(k) with a company match