AI Technical Product Manager, Dean's Office

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 Harvard Business School? Harvard Business School, located on a 40-acre campus in Boston, was founded in 1908 as part of Harvard University. It is among the world's most trusted sources of management education and thought leadership. For more than a century, the School's faculty has combined a passion for teaching with rigorous research conducted alongside practitioners at world-leading organizations to educate leaders who make a difference in the world. 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. Job Description 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 Qualifications 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. Additional Information 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.