AI Technical Product Manager, Dean's Office
Job description
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
Basic
Qualifications
- Minimum of five years’ post-secondary education or relevant work experience
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 Qualifications and
Skills
- Data science background with tech development experience
- Master's preferred
- 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.)
Key Competencies
- Technical depth - Ability to engage credibly with AI/ML engineers on architecture and implementation details
- Strategic thinking - Seeing beyond immediate features to long-term product evolution as identified by Project Director
- Motivation and problem solving– empowering technical team to overcome real or perceived barriers to execute on time
- User understanding – Working with UX/UI team to translate complex AI capabilities into intuitive user experiences
- Data-driven decision making - Using metrics and experimentation to validate hypotheses
- Communication - Explaining technical concepts clearly to diverse audiences
- Adaptability - Thriving in the rapidly evolving AI landscape
This role requires someone who is equally comfortable discussing neural network architectures with engineers and working with business team members, serving as a crucial link between AI innovation and product success.
- Appointment End Date: This position is approved for a (2)-year term (with possibility of
- renewal/extension) which begins on the person's first day of employment.
- 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
- 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 allstaff 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.
- A cover letter is required to be considered for this opportunity.
#LI-MM1
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 058. 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.
Skills mentioned
- Ab Testing
- Acceptance Criteria
- Agile
- AI
- AWS
- Azure
- Cloud
- Computer Vision
- Data Engineering
- Data Pipelines
- Data Science
- GCP
- Generative AI
- Governance
- KPI Reporting
- LLM
- Machine Learning
- Mlops
- Model Deployment
- Neural Networks
- NLP
- Product Management
- Prompt Engineering
- PyTorch
- Rag
- Risk Management
- Scikit Learn
- Stakeholder Management
- TensorFlow
- UI UX Design
- User Stories
- Zoom

In 1636, just sixteen years after the Pilgrims landed at Plymouth, the Great and General Court of the Massachusetts Bay Colony voted to establish what would become Harvard College in Newtowne (now Cambridge), Massachusetts. The colonial leaders recognized a critical gap: the growing colony needed educated clergy and civil leaders who could sustain their young society. The institution found its enduring identity in 1638 when John Harvard, a young minister, bequeathed half his estate and his library of over 400 books to the fledgling college - giving it his name and establishing a tradition of philanthropic support that would sustain it for nearly four centuries. From those humble origins with nine students and one master, Harvard has evolved into a world-renowned research university comprising fourteen schools that educate over 24,000 students annually. The university has expanded from its original focus on training ministers to producing leaders across every field of human endeavor - science, law, medicine, business, government, and the arts. Today, Harvard stands as the oldest institution of higher learning in the United States, driven by an unwavering commitment to excellence in teaching, research, and the development of leaders who make a difference globally. Its community of 400,000-plus alumni worldwide and 20,667 faculty and staff continue to push the boundaries of knowledge while addressing humanity's most pressing challenges.
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