AI Technical Product Manager

Company Description

By working at Harvard University, you join a vibrant community that advances Harvard's world-changing mission in meaningful ways, inspires innovation and collaboration, and builds skills and expertise. We are dedicated to creating a diverse and welcoming environment where everyone can thrive.

Why join HBS Foundry?

HBS Foundry is a new initiative at Harvard Business School that helps founders build, fund, and launch their ventures through an AI-driven digital learning platform. We’re a small, collaborative team within one of the world’s most respected institutions—combining the energy of a startup with the mission and reach of Harvard. Foundry brings together educators, engineers, and creative thinkers who are passionate about innovation, learning, and impact. Together, we’re developing tools and experiences that empower founders to grow their ventures and their confidence. It’s an exciting, fast-moving environment where new ideas matter and every team member has the opportunity to shape what comes next.

Job Summary

As an AI Technical Product Manager, you will lead the development and implementation of complex information technology projects to solve problems with wide impact. This role requires high levels of functional integration and managing multiple disciplines, potentially across several simultaneous projects. You will bridge the gap between artificial intelligence capabilities and real-world product applications, combining deep technical understanding with strategic product insight 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, determine their applicability, 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 consideration. 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.

Qualifications

Basic Qualifications:

• Minimum of seven years’ post-secondary education or relevant work experience.

Additional Qualifications and Skills:

• Knowledge of Microsoft Office Suite, advanced Excel skills.
• Knowledge of information technology applications, processes, software and equipment.
• Highly specialized knowledge of a specific technology.
• Knowledge of advanced IT project management principles (e.g. Agile) and software.
• Demonstrated cross-functional project management experience.
• Demonstrated team performance skills, service mindset approach, and the ability to act as a trusted advisor.
• Attitude that supports an Agile working environment.
• Master's degree in Computer Science, Engineering, Data Science, or related technical field.
• Experience with large language models, prompt engineering, or RAG systems.
• Background in software engineering or data science.
• Track record of managing products at scale with millions of users.
• Exposure navigating AI regulatory landscapes (EU AI Act, etc.).

Technical Background:

• 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 products.
• Strong understanding of machine learning concepts, algorithms, and deployment architectures.
• Experience with AI/ML tools and frameworks (TensorFlow, PyTorch, scikit-learn, etc.).
• Familiarity with cloud platforms (AWS, Azure, GCP) and MLOps practices.

Product Management Skills:

• Proven track record of shipping successful AI-powered products from concept to launch.
• Expertise in agile methodologies and product development frameworks.
• Excellent stakeholder management and communication abilities.

Domain Knowledge:

• Understanding of AI applications in relevant industry verticals.
• Knowledge of generative AI, NLP, computer vision, or other specialized AI domains as applicable.
• Awareness of AI ethics, bias mitigation, and responsible AI principles.

Additional Information

This is a hybrid position, requiring a minimum of 3 days per week onsite at the Boston, MA campus. Specific hours and days are determined by business needs. A cover letter is required for consideration. Candidates are required to complete a Take Home Assignment after clearing the Technical Recruiter Screen.

Key skills/competency

• AI Product Management
• Machine Learning
• Cross-functional Collaboration
• Agile Methodologies
• Stakeholder Management
• Generative AI
• Data Science
• MLOps
• Ethical AI
• Product Development