AI Technical Product Manager, Dean's Office

Job Summary:

The AI Technical Product Manager bridges the gap between artificial intelligence capabilities and real-world product applications, combining deep technical understanding with strategic product understanding to build AI-powered solutions that deliver measurable value.

Job-Specific Responsibilities:

Product

• Balance innovation with practical implementation, assessing technical feasibility and business impact

• Establish success metrics and KPIs for AI product initiatives

Technical Leadership

• Collaborate with data scientists, ML engineers, and software developers to translate business requirements into technical specifications

• Understand AI/ML fundamentals including model architectures, training processes, evaluation metrics, and deployment considerations

• Make informed decisions about model selection, data requirements, and infrastructure needs

• Evaluate emerging AI technologies and determine their applicability to product challenges and understand risk mitigation strategies.

Cross-Functional Collaboration

• Partner with engineering teams to prioritize features and manage the development lifecycle

• Work with design teams to create intuitive user experiences that leverage AI capabilities effectively

• Coordinate with data engineering on data pipelines, quality, and governance

• Communicate technical concepts to non-technical stakeholders including executives and customers

Product Development & Execution

• Align with Project Director on strategic priorities, customer experience and usability needs, and internal / external deadlines.

• Own the product backlog, writing detailed user stories and acceptance criteria for AI features

• Manage tradeoffs between model performance, latency, cost, and user experience

• Oversee A/B testing and experimentation frameworks to validate AI-driven improvements

• Monitor model performance in production and coordinate retraining or optimization efforts

Ethics & Risk Management

• Ensure responsible AI practices including fairness, transparency, and privacy considerations

• Identify potential biases in training data and model outputs

• Establish governance frameworks for AI model deployment and monitoring

• Navigate regulatory requirements, security needs, and compliance considerations

• Build trust and collaboration by being present on-site and engaging directly with 

colleagues and various constituents.

• This role is responsible for other duties as assigned