Markets Product Manager, Assistant Vice President
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Looking for an AI product manager job in Boston? Choose from 34 open roles at 17 employers. Explore real salary data and skills breakdown across remote, hybrid and on-site roles.
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As of 23 September, 19 AI product manager roles are open in Boston at 11 employers. 1 new roles have been posted since 21 September. Of the roles that say how they work, 37% are remote or hybrid.
Among the AI product manager roles listed on the board, the majority sit at senior level, with roughly a quarter at mid level and the remainder at lead. Most of the openings were posted some time ago, with only a small minority appearing within the past month or this week, suggesting hiring has been relatively measured rather than a burst of new activity. A notable share of roles is concentrated among a handful of employers. Agents and APIs appear in more than a fifth of role descriptions, alongside mentions of large language models and cloud infrastructure. There is not enough weekly history yet to say whether the number of openings is rising or falling.
Figures are measured every Monday.
An AI product manager defines and steers the development of AI-powered features or products, working between technical teams, designers and business stakeholders. The role typically involves translating research capabilities into usable product requirements, setting priorities, and tracking whether shipped features meet the intended goals. In a city where hospitals, biomedical research and financial services are prominent employers, AI product managers often work on highly regulated or data-sensitive applications. Northeastern University's Institute for Experiential AI, for example, focuses applied AI efforts on health and life sciences, areas that reflect the kinds of product contexts common here. Managing relationships with scientific or clinical counterparts is therefore a common element of the work.
Descriptions on the board mention AI agents and API integration most frequently, suggesting candidates should be comfortable reasoning about how AI systems connect to external services and workflows. Large language models and retrieval-augmented generation appear in a portion of descriptions, so familiarity with how these models are built and evaluated is useful. Cloud platforms and infrastructure terms also appear, indicating that understanding how products are deployed at scale is valued, even if hands-on engineering is not the primary expectation.
The employers' own advertised ranges, for individual roles at different levels — not an average and not a market rate.
Among roles on the board that state a work mode, nearly two thirds call for fully on-site presence, and about a third are hybrid. Remote-only positions make up a small minority. This balance reflects the collaborative and stakeholder-facing nature of product roles, as well as the proximity many employers expect to research, clinical or trading-floor environments.
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