AI Technical Product Manager, Dean's Office
Listed on 2026-11-01
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IT/Tech
AI Business & Operations -
Business
AI Business & Operations
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Through a dynamic ecosystem of research, learning, and entrepreneurship that includes MBA, Doctoral, Executive Education, and Online programs, as well as numerous initiatives, centers, institutes, and labs, Harvard Business School fosters bold new ideas and collaborative learning networks that shape the future of business.
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
- 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.
- 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
- 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
- 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
- Minimum of five years' post-secondary education or relevant work experience
- Bachelor's degree in Computer Science, Engineering, Data Science, or related technical field
- 5+ years of product management experience with 2+ years specifically on AI/ML…
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