Sr. Manager, AI Lead - Semantic Layer - Remote

CSAA Insurance Group, a AAA Insurer•Washington, DC

5d•$168,300 - $224,300•Remote

About The Position

CSAA Insurance Group is seeking an experienced AI Lead Manager to lead the development and evolution of its semantic data products—an essential enterprise capability that connects data, business concepts, and AI-driven experiences across the organization. Sitting within IT and partnering closely with business, data, and technology leaders, this role will define and operationalize a shared semantic foundation, establishing consistent definitions for core business entities such as customers, policies, and claims, and mapping their relationships across systems. As the product owner, this leader will drive vision, strategy, roadmap, and adoption, translating complex business and technical needs into a scalable, governed, and business-aligned product that powers search, analytics, automation, interoperability, and generative AI use cases. In strong alignment with Enterprise Architecture and Data leadership, this role ensures semantic capabilities support long-term enterprise strategy while applying a “data as a product” mindset. The position also includes mentoring and growing a team of product managers, strengthening product discipline and execution, and delivering measurable value through improved decision-making, intelligent workflows, and a scalable foundation for enterprise data and AI innovation.

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
Applicants must have authorization to work indefinitely in the US.
Please do not apply for this role if at any time (now or in the future) you will need immigration support (i.e., H-1B, TN, STEM OPT Training Plans, etc.).

Nice To Haves

Experience leading or mentoring product managers or cross-functional teams preferred
Creates a collaborative, inclusive and psychologically safe environment, demonstrating authenticity and fostering trust to inspire and empower team members and colleagues
Actively shapes our company culture through words and actions (e.g., supporting employee resource groups, mentoring employees, volunteering, joining cross-functional projects, encouraging team member involvement in these activities)
Champions our cultural norms (e.g., willing to have cameras when it matters: interviewing candidates, building relationships with team members, etc.)
Translates our enterprise strategy and priorities for their team members to connect to the bigger picture
Demonstrates a company ownership mindset, thinking beyond boundaries of their own area
Travels as needed for role, including enterprise meetings, divisional / team meetings, and other in-person meetings
Fulfills business needs, which may include investing extra time, helping other teams, etc.

Responsibilities

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.
Partner with data engineering, enterprise architecture, and AI/ML teams to translate business concepts into scalable technical implementations.
Partner with Architecture and Data teams to ensure data exposed through APIs and integration layers is consistently structured, well-governed, and aligned to shared business definitions and use cases.
Act as the connective layer between business partners and technical teams.
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.
Ensure compliance with regulatory and data privacy requirements.