AI Product Manager - Insurance Domain

Description:

The ideal candidate will bring a strong focus on building production-worthy, measurable, and continuously improving AI products.

Key Responsibilities:

- Define and Champion: Develop the vision, strategy, and roadmap for AI-powered products that align with the company's strategic goals in the insurance sector.

- Opportunity Identification: Conduct research and analysis to identify high-impact opportunities where AI/ML can create significant business value to our companies and customers.

2. Hands-on AI Solution Development and Prototyping:

- Technical Problem Solving (Hands-on): Be very hands-on in trying to solve insurance problems by directly experimenting with and applying various AI models (LLMs, computer vision, traditional ML) and tools.

- Rapid Prototyping: Rapidly prototype and test AI solutions to validate their technical feasibility and business impact before full-scale development.

- AI/ML Concepts: An understanding of AI Agents, their application in enterprise systems, and familiarity with concepts like MCP Servers and context engineering.

3. Productionization and Evaluation (Evals):

- Building Production-Worthy Solutions: Own the end-to-end lifecycle of AI models, ensuring they transition smoothly from experimentation to robust, scalable production systems.

- Evaluation Frameworks (Evals): Design, implement, and own rigorous AI evaluation frameworks to ensure that all AI solutions meet high standards for accuracy, fairness, robustness, and business impact before and after deployment.

4. Continuous Improvement and Iteration:

- Performance Monitoring: Establish continuous monitoring of deployed AI models to detect performance degradation (model drift) and data quality issues.

- Responsible AI: Ensure all AI products adhere to ethical guidelines, regulatory requirements, and internal responsible AI principles, with a focus on explainability and bias mitigation