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Senior Manager, AI Lead – Semantic Layer
Location
Alabama + 23 moreAll locations: Alabama | Arizona | California | Colorado | Connecticut | District Of Columbia | Florida | Idaho | Illinois | Iowa | Kansas | Kentucky | Louisiana | Maine | Montana | Maryland | Massachusetts | Michigan | Minnesota | Mississippi | Missouri | South Carolina | Virginia | Washington
Posted
64 days ago
Salary
$168.3K - $224.3K / year
Seniority
Senior
Job Description
Senior Manager, AI Lead – Semantic Layer
AAA
• 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
Job Requirements
- 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
- total compensation package
- annual bonus eligibility for most roles
- 401(k) with a company match
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