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Harvard Business School

AI Technical Product Manager, HBS Foundry

Posted 22 Days Ago
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In-Office
Boston, MA
Senior level
In-Office
Boston, MA
Senior level
The AI Technical Product Manager will lead AI product initiatives, balancing innovation with implementation, collaborating with technical teams, and ensuring responsible AI practices.
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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 Description

Job Summary:

Lead development and implementation of complex information technology projects to solve problems that may have wide impact, requiring high levels of functional integration and involving multiple disciplines to be managed.  May manage a number of projects simultaneously.

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 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

  • Appointment End Date: This position is approved as a term appointment with an end date of June 30, 2027. There is a possibility of renewal/extension.
  • Standard Hours/Schedule: 40 hours per week
  • Visa Sponsorship Information: Harvard University is unable to provide visa sponsorship for this position
  • Pre-Employment Screening: Identity, Education, Criminal
  • Other Information:
    • This is a hybrid position which we consider to be a combination of remote and onsite work at our Boston, MA based campus. HBS expects all staff to be onsite a minimum of 3 days per week and departments provide onsite coverage Monday – Friday. Specific hours and days onsite will be determined by business needs and are subject to change with appropriate advanced notice.
    • We may conduct candidate interviews virtually (phone and/or via Zoom) and/or in-person for this role
    • As part of our evaluation, candidates are required to complete a Take Home Assignment after clearing Technical Recruiter Screen. This assignment will test your specific skills/knowledge areas relevant to the role.
    • A cover letter is required to be considered for this opportunity 

Work Format Details

This position has been determined by school or unit leaders that some of the duties and responsibilities can be effectively performed at a non-Harvard location. The work schedule and location will be set by the department at its discretion and based upon operational needs. When not working at a Harvard or Harvard-designated location, employees in hybrid positions must work in a Harvard registered state in compliance with the University’s Policy on Employment Outside of Massachusetts. Additional details will be discussed during the interview process. Certain visa types and funding sources may limit work location. Individuals must meet work location sponsorship requirements prior to employment.

Salary Grade and Ranges

This position is salary grade level 059. Please visit  Harvard's Salary Ranges  to view the corresponding salary range and related information. 

Benefits

Harvard offers a comprehensive benefits package that is designed to support a healthy work-life balance and your physical, mental and financial wellbeing. Because here, you are what matters. Our benefits include, but are not limited to: 

  • Generous paid time off including parental leave 
  • Medical, dental, and vision health insurance coverage starting on day one 
  • Retirement plans with university contributions 
  • Wellbeing and mental health resources 
  • Support for families and caregivers 
  • Professional development opportunities including tuition assistance and reimbursement 
  • Commuter benefits, discounts and campus perks 

Learn more about these and additional benefits on our Benefits & Wellbeing Page. 

EEO/Non-Discrimination Commitment Statement

Harvard University is committed to equal opportunity and non-discrimination. We seek talent from all parts of society and the world, and we strive to ensure everyone at Harvard thrives. Our differences help our community advance Harvard's academic purposes.

Harvard has an equal employment opportunity policy that outlines our commitment to prohibiting discrimination on the basis of race, ethnicity, color, national origin, sex, sexual orientation, gender identity, veteran status, religion, disability, or any other characteristic protected by law or identified in the university's non-discrimination policy. Harvard's equal employment opportunity policy and non-discrimination policy help all community members participate fully in work and campus life free from harassment and discrimination.

Top Skills

Agile
AI
AWS
Azure
Excel
GCP
Machine Learning
Microsoft Office Suite
PyTorch
Scikit-Learn
TensorFlow
HQ

Harvard Business School Boston, Massachusetts, USA Office

Soldiers Field Road, Boston, MA, United States, 02163

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