Develop and implement AI risk assessment and pricing frameworks by evaluating AI models, creating rating tables and pricing models, collaborating with underwriters, building Python-based analytical tools, and researching emerging AI risks and mitigation strategies.

Conduct research into AI model behavior and failure modes; design and build models, agents, and automated evaluation pipelines to assess AI risk; develop production-grade tooling for continuous monitoring and model testing; create novel risk metrics; collaborate with underwriting and actuarial teams to translate findings into pricing signals; prototype and deploy robust, well-tested systems while communicating results to technical and non-technical stakeholders.

Design, build, and maintain adversarial AI evaluation platforms and AI pipelines. Implement software engineering best practices for ML, integrate UI/UX, deploy on major cloud providers, and collaborate cross-functionally to improve model robustness and product infrastructure.