Design, build, and evaluate generative AI and agentic systems; develop enterprise semantic layers and knowledge graphs; create GenAI evaluation frameworks assessing performance, reliability, and safety; collaborate across data science, engineering, and business teams; champion best practices; lead cross-functional working groups; communicate technical findings; and provide technical consulting on high-impact initiatives.

Develop predictive pricing and underwriting models for property and specialty insurance products. Responsibilities include manipulating large datasets, testing hypotheses, evaluating statistical significance, creating visualizations, supporting pricing program deployments, adjusting models for state regulations, preparing regulatory documentation, and responding to Department of Insurance objections. The role collaborates with business stakeholders and data science teams to deliver data-driven solutions and explain technical findings to nontechnical audiences.

Own backlog prioritization and delivery for AI platform capabilities (MCP connectors, ingestion pipelines, platform enablement). Translate prototypes into requirements, coordinate delivery across Technology, Security, and Investment teams, monitor production health, run UAT, manage governance (RAIC) submissions, and drive iterative improvements and documentation to support adoption.