Jobs / United States / Harvard University
AI Technical Product Manager, Dean's Office
Harvard University · 🇺🇸 Boston, MA, US
Sponsorship verdict
Sponsorship possible
One solid signal, not two — worth applying, and worth asking about sponsorship early.
- Employer is on a government sponsor recordThe US Department of Labor certified 123 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first. USCIS also records 73 H-1B approvals in FY2023. Source: LCA disclosure data (US Department of Labor (OFLC)).
- The posting doesn’t mention sponsorshipSilence isn’t a refusal — ask the recruiter before investing much time.
- No salary bar for this routeH-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area. Cap-subject employers enter a lottery weighted by wage level. Source: https://www.federalregister.gov/documents/2025/12/29/2025-23853/weighted-selection-process-for-registrants-and-petitioners-seeking-to-file-cap-subject-h-1b, rules effective 2026-02-27.
- Confirmed live todayWhen a source last listed this job as open.
US H-1B: cap-subject employers enter a lottery weighted by wage level — Level I gets 1 entry, Level IV gets 4 (DHS projected selection odds ≈15% at Level I to ≈61% at Level IV). Universities and non-profit research employers are cap-exempt. The $100,000 fee for new petitions from abroad is currently blocked by a court order (appeal pending).
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Sponsor Radar — Harvard University
The US Department of Labor certified 123 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first. USCIS also records 73 H-1B approvals in FY2023. Source: LCA disclosure data (US Department of Labor (OFLC)).
Past sponsorship or register membership never guarantees sponsorship for this vacancy or for you. Full Sponsor Radar for Harvard University →
About the role
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 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 s