Program Manager, Frontier AI Assistants Enablement

Suffolk Construction•Boston, MA

5d•Hybrid

About The Position

We are seeking a Program Manager, Frontier AI Assistants Enablement to support the rollout, adoption, and ongoing management of general-purpose AI assistants across the organization, including ChatGPT Enterprise, Claude Enterprise, and Microsoft Copilot. This role is focused on helping employees understand and apply approved AI assistants in their day-to-day work. The Program Manager will support license management, feature enablement, governance coordination, usage reporting, training, office hours, user feedback, and adoption programs that help employees use AI assistants responsibly and effectively. The ideal candidate is highly organized, collaborative, detail-oriented, curious about AI, and energized by helping others learn and adopt new ways of working.

Requirements

5–8 years of experience in technology, program management, digital enablement, enterprise applications, product operations, or a related role; or equivalent management experience in construction and a Bachelor’s degree in a quantitative field such as Statistics, Mathematics, Economics, Computer Science, Engineering, Data Science, Finance, or a related discipline.
Experience with ChatGPT Enterprise, Claude Enterprise, Microsoft Copilot, or similar general-purpose AI assistants.
Experience driving adoption, training, enablement, or change management for technology tools or business applications.
Strong AI user with demonstrated familiarity using general-purpose AI assistants, including the ability to apply them effectively to day-to-day work and evaluate new capabilities.
Experience supporting enterprise technology tools, including user access, licensing, feature configuration, reporting, and vendor coordination.
Strong program management skills, including planning, stakeholder management, execution, documentation, and follow-through.
Ability to work cross-functionally with IT, security, data, engineering, learning and development, operational excellence, communications, and business teams.
Strong analytical skills, with the ability to interpret usage data, adoption metrics, license utilization, spend, and user feedback.
Excellent communication and facilitation skills, including the ability to lead office hours, trainings, workshops, demos, and stakeholder discussions.
High attention to detail, curiosity about emerging AI capabilities, and comfort

Nice To Haves

Familiarity with responsible AI usage, data privacy, security reviews, enterprise technology controls, and safe enablement practices.
Familiarity with automation, low-code/no-code tools, or agentic AI workflows.
Experience creating adoption dashboards or reporting on usage, licenses, spend, training participation, or business impact.
Experience in a large enterprise environment with multiple stakeholder groups and governance requirements.

Responsibilities

Support day-to-day management of general-purpose AI assistants, including license allocation, user access, feature availability, configuration, and vendor coordination.
Partner with IT, security, legal, data, and AI engineering teams to evaluate and enable AI assistant features in a safe, scalable, and compliant way.
Monitor usage, adoption, license utilization, token consumption, spend, and other operational metrics.
Help develop processes to improve visibility into AI assistant usage, adoption patterns, and business value.
Stay current on updates, features, vendor roadmaps, and emerging capabilities across frontier AI assistants.
Design and coordinate enablement programs for different user groups, from foundational users to advanced power users.
Run office hours, workshops, demos, and role-specific training sessions.
Lead and support an AI Champions group to scale awareness, adoption, and responsible usage across teams.
Interview users and stakeholders to understand needs, adoption barriers, workflow opportunities, and support requirements.
Partner with Learning & Development, Operational Excellence, change management, communications, IT, data, and AI engineering teams to support adoption.
Coordinate pilots for new AI assistant features or tools, gather feedback, document lessons learned, and recommend next steps.
Define and track adoption metrics, usage trends, engagement levels, and indicators of business impact.