AI Product Manager
Delhi
Product
1 Openings
About the Role
We are seeking a highly motivated and technically proficient AI Product Manager to drive the development and deployment of cutting-edge artificial intelligence solutions within the insurance domain. This is a hands-on role for a product leader who is passionate about leveraging AI to solve complex business problems, across the insurance value chain.
The ideal candidate will bring a strong focus on building production-worthy, measurable, and continuously improving AI products.
Key Responsibilities
1\. AI Product Strategy and Vision
• 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.
• Model Selection and Vetting: Continuously check the performance of various
models and tools available in the market to build organizational intelligence on the
best models for different types of insurance problems.
• 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.
• Metric Definition: Define and track both technical metrics and business metrics to
measure the success of AI products.
4\. Continuous Improvement and Iteration
• Performance Monitoring: Establish continuous monitoring of deployed AI models
to detect performance degradation (model drift) and data quality issues.
• Iterative Improvement: Continuously iterate on deployed solutions based on
performance data, A/B testing results, and user feedback to drive measurable
improvements in model performance and business outcomes.
• 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.
Required Qualifications
• Experience: 4+ years of experience in Product Management, with at least 6
months building AI powered products.
• Proven Track Record: Must have a proven track record of building and successfully
launching production-grade AI solutions that have delivered measurable business
value.
• Hands-on Tooling: Demonstrated experience using and evaluating various AI tools,
models, and platforms (e.g., cloud services, open-source libraries, LLMs, vector
databases).
• Technical Fluency: Strong technical background with a deep understanding of the
AI/ML lifecycle, including data pipelines, model training, deployment, and
monitoring is a plus.
• Domain Knowledge: Experience in Insurance, FinTech, is a significant advantage.
We are seeking a highly motivated and technically proficient AI Product Manager to drive the development and deployment of cutting-edge artificial intelligence solutions within the insurance domain. This is a hands-on role for a product leader who is passionate about leveraging AI to solve complex business problems, across the insurance value chain.
The ideal candidate will bring a strong focus on building production-worthy, measurable, and continuously improving AI products.
Key Responsibilities
1\. AI Product Strategy and Vision
• 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.
• Model Selection and Vetting: Continuously check the performance of various
models and tools available in the market to build organizational intelligence on the
best models for different types of insurance problems.
• 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.
• Metric Definition: Define and track both technical metrics and business metrics to
measure the success of AI products.
4\. Continuous Improvement and Iteration
• Performance Monitoring: Establish continuous monitoring of deployed AI models
to detect performance degradation (model drift) and data quality issues.
• Iterative Improvement: Continuously iterate on deployed solutions based on
performance data, A/B testing results, and user feedback to drive measurable
improvements in model performance and business outcomes.
• 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.
Required Qualifications
• Experience: 4+ years of experience in Product Management, with at least 6
months building AI powered products.
• Proven Track Record: Must have a proven track record of building and successfully
launching production-grade AI solutions that have delivered measurable business
value.
• Hands-on Tooling: Demonstrated experience using and evaluating various AI tools,
models, and platforms (e.g., cloud services, open-source libraries, LLMs, vector
databases).
• Technical Fluency: Strong technical background with a deep understanding of the
AI/ML lifecycle, including data pipelines, model training, deployment, and
monitoring is a plus.
• Domain Knowledge: Experience in Insurance, FinTech, is a significant advantage.
Recruitment Notice
“Due to high interest, our team connects only with candidates whose profiles closely match the role mandate.”
Exploring your next leadership move?
Most leadership roles never reach job boards. ExecEdge helps senior professionals access the hidden leadership market through positioning, outreach, and warm introductions.