Senior Project Manager - Responsible AI, Information Technology

About the role:

Artificial intelligence is becoming increasingly embedded across medical technology, enterprise operations, digital health, clinical workflows, and customer-facing solutions. Boston Scientific is advancing science for life by enabling AI innovation through clear governance, accountable decision-making, and responsible AI practices that scale across the enterprise.

As a Senior Project Manager, Responsible AI, you will act as a process steward to evangelize Responsible AI (RAI) governance and operationalize the cross-functional governance model for AI across Boston Scientific. You will translate high-level policies and workflows into a highly adopted, well understood, scalable, metrics-driven program that ensures appropriate governance for every AI initiative across divisions, regions, and functions.

In this role, and using change enablement practices, you will assist teams hands on to achieve full organizational implementation, adoption, and practice of Responsible AI processes. You will work closely with the Responsible AI team and Council, AI Engineering, Enterprise Architecture, Data and AI Governance, Legal, Privacy, Security, Regulatory, Quality, Compliance, and divisional business stakeholder teams to embed Responsible AI controls into AI solutions and products while enabling teams to move with speed and clarity.

Work model, sponsorship, relocation:

At Boston Scientific, we value collaboration and synergy. This role follows a hybrid work model requiringemployees to be in our local office at least three days per week. Boston Scientific will not offer sponsorship or takeover sponsorship of an employment visa for this position at this time.

Your responsibilities will include:

Responsible AI process stewardship and hands-on project enablement

• Develop deep expertiseand enablement readiness for the end-to-end Responsible AI process, requirements, decision points, roles, artifacts, controls, and escalation pathways.

• Partner hands on with AI project teams from intake through approval and ongoing governance, helping each team understand requirements, complete required activities and documentation, engage the right reviewers, resolve issues, and reach full compliance efficiently.

• Act as a trusted guide and primary process resource for project teams, translating Responsible AI policies and compliance requirements into clear, practical actions tailored to the project’s use case, risk profile, development pathway, and business context.

• Proactively identify blockers, unclear requirements, missing inputs, dependencies, and decision needs; coordinate with Responsible AI, Legal, Privacy, Security, Regulatory, Quality, Compliance, Data and AI Governance, Enterprise Architecture, and other stakeholders to keep projects moving.

Role definition, operating model, and scalable playbook

• Define and continuously refine the responsibilities, engagement model, success pathways, standard work, service expectations, and decision/escalation mechanisms based on practical experience supporting AI projects.

• Establish a repeatable operating model for how process stewards engage with AI initiative owners, governance reviewers, and compliance functions, including entry criteria, checkpoints, handoffs, communication expectations, and completion criteria.

• Collaborate closely with the change enablement team to incorporate the RAI process within existing governance processes; design a framework that enables high process adoption, including creating a comprehensive playbook, including process maps, role guides, checklists, templates, FAQs, examples, training content, facilitation guidance, and lessons learned.

• Design the role and playbook for enterprise scale so the capability can be replicated across divisions, regions, and functions while maintaining consistent Responsible AI standards and outcomes.

• Identifyexisting and design new cohortsthrough whicha successful implementation ofthe capability androle as well as a global RAI enablementcommunitycan be delivered at scale

Compliance performance, process improvement, and program delivery

• Drive toward 100% adherence to applicable Responsible AI process requirements for supported projects, with clear visibility to project status, required actions, accountable owners, risks, exceptions, and completion.

• Track and analyze process performance, including compliance rates, cycle times, aging, rework, recurring questions, handoff delays, and bottlenecks; use insights to reduce avoidable process delays while maintaining governance rigor.

• Partner with Responsible AI process owners and cross-functional compliance teams to identify opportunities to simplify, clarify, standardize, and improve workflows, documentation, guidance, and controls.

• Build and present implementation plans, operating proposals, progress updates, metrics, risks, and recommendations to program leaders and stakeholders, demonstrating value and informing decisions about expansion of the capability.

Change enablement, communication, and capability building

• Evangelize the Responsible AI process through clear, credible communications that explain the value of the RAI enablement role, how teams should engage, and how strong governance can enable responsible innovation with greater speed and predictability.

• Develop and deliver practical training, office hours, coaching, workshops, and other enablement mechanisms that help AI project teams and future RAI SMEs confidently navigate Responsible AI requirements.

• Build strong relationships across business, technology, and compliance functions; influence without direct authority and facilitate alignment when requirements, ownership, or pathways are ambiguous.

• Capture feedback and lessons learned from project teams and reviewers and translate them into continuous improvements to the RAI SME role, playbook, training, and Responsible AI operating model.

Required qualifications:

• Minimum Bachelor's degree in Business, Engineering, Computer Science, Data Science, Biomedical Engineering, Public Policy, Law, Ethics, or a related field.

• Minimum 7 years of experience in project/program management, governance, risk management, compliance, quality, regulatory, privacy, security, digital delivery, or AI/data-enabled transformation within a large, matrixed organization; healthcare, medtech, life sciences, or another regulated industry strongly preferred.

• Demonstrated experience navigating and operationalizing complex compliance or governance processes, with the ability to quickly learn detailed requirements and translate them into clear, practical guidance for delivery teams.

• Strong project and program management capabilities, including planning, workflow management, dependency and issue resolution, stakeholder coordination, escalation, metrics, agile deliveryand measurable outcome delivery.

• Excellent written, verbal, facilitation, and presentation skills, with demonstrated ability to communicate complex requirements clearly to technical, business, compliance, and executive audiences.

• Demonstrated ability to build new operational programs or capabilities from an emerging model, including defining roles, standard work, success measures, implementation plans, and scalable ways of working.

• Strong change management and stakeholder engagement skills, including the ability to drive adoption, coach teams, build credibility, influence without direct authority, and champion a new role or process across an organization.

Preferred qualifications:

• Experience with Responsible AI, AI governance, model risk management, data governance, technology risk, or other AI-related compliance processes.

• Working knowledge of AI/ML solution delivery and relevant risk domains, including privacy, cybersecurity, quality, regulatory, data governance, and risk-based controls.

• Familiarity with emerging AI regulatory and standards landscapes, such as the EU AI Act, NIST AI Risk Management Framework, ISO/IEC AI standards, FDA considerations for AI-enabled medical software, or related responsible technology frameworks.

• Experience developing playbooks, standard operating models, process documentation, training, communications, or change enablement materials for enterprise programs.

• Experience defining and using compliance and operational metrics, dashboards, service measures, or continuous-improvement methods to improve process performance and reduce cycle time.

• Certification or formal training in Project/Program Management, Agile, Change Management, Risk Management, Privacy, Security, Quality, Regulatory, or Compliance (e.g., PMP, Prosci, SAFe, or equivalent).