Additional Location(s): N/A
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 the Program Manager, Responsible AI, you will oversee and manage Responsible AI (RAI) governance and operationalize the cross-functional governance model for AI across Boston Scientific. You will translate high-level policies and partially defined workflows into a scalable, metrics-driven program that ensures appropriate governance for every AI initiative across divisions, regions, and functions.
In this role, you will lead implementation, launch, and scale of Responsible AI policies, workflows, processes, compliance metrics, and reporting mechanisms. You will work closely with AI Engineering, Enterprise Architecture, Data and AI Governance, Legal, Privacy, Security, Regulatory, Quality, Compliance, and divisional business teams to embed Responsible AI controls into practical delivery processes while enabling teams to move with speed and clarity.
Work ModeAt Boston Scientific, we value collaboration and synergy. This role follows hybrid work model, requiring employees to be in our local office three days per week.
RelocationRelocation assistance is not available for this position at this time.
VISABoston Scientific will not offer sponsorship or take over sponsorship of an employment VISA for this position at this time.
Your responsibilities will include:Responsible AI governance operations- Lead and organize the cross-functional Responsible AI Governance teams, including charter, operating cadence, agendas, decision logs, action tracking, escalation pathways, and leadership reporting.
- Operationalize the governance team by coordinating participation across AI, Data Governance, Legal, Privacy, Security, Regulatory, Quality, Compliance, Enterprise Architecture, and divisional stakeholders.
- Lead implementation, launch, and scale of Responsible AI policies and workflows, translating high-level policy requirements and partially defined processes into repeatable enterprise operating models.
- Establish clear roles, responsibilities, decision rights, and governance forums so AI initiatives can move efficiently through intake, review, approval, monitoring, and escalation.
Enterprise AI governance program delivery- Create and manage a scalable governance program for AI initiatives across all divisions, regions, and functions, ensuring each initiative follows the appropriate Responsible AI pathway based on risk, use case, data sensitivity, and regulatory impact.
- Develop standardized intake, triage, risk assessment, documentation, workflow, and approval artifacts that can be reused across business units and integrated into existing product, data, technology, and compliance processes.
- Partner with cross-functional teams to embed Responsible AI requirements into agile delivery, product development, vendor onboarding, data governance, cybersecurity, privacy, quality, and software lifecycle processes.
- Maintain an enterprise view of AI initiatives progressing through governance, including status, risks, decisions required, accountable owners, dependencies, and readiness for launch or scale.
Metrics-driven compliance and reporting- Define and implement governance KPIs and compliance metrics that measure Responsible AI workflow adherence, review cycle times, risk disposition, overdue actions, control effectiveness, and adoption across the enterprise.
- Build and maintain reporting mechanisms, dashboards, and executive summaries that provide visibility into Responsible AI governance performance, emerging risks, program maturity, and decision needs.
- Use metrics and feedback to identify bottlenecks, policy gaps, process variation, training needs, and opportunities to improve speed, consistency, and quality of AI governance decisions.
Stakeholder enablement and change management- Enable divisional and functional teams to navigate Responsible AI governance requirements by providing playbooks, templates, process guidance, training materials, and practical support for AI initiative owners.
- Facilitate cross-functional alignment on complex or ambiguous AI use cases, helping teams clarify risks, controls, accountable owners, and decisions required to advance responsibly.
- Communicate program updates, risks, milestones, and trade-offs to senior leaders and governance stakeholders, ensuring timely decisions and transparent accountability.
- Drive continuous improvement of the Responsible AI operating model as regulations, enterprise standards, technologies, and business needs evolve.
Required qualifications:- Bachelor's degree in Business, Engineering, Computer Science, Data Science, Biomedical Engineering, Public Policy, Law, Ethics, or a related field.
- 7+ years of experience in program management, product management, governance, risk management, compliance, digital delivery, or AI/data-enabled transformation within a large, matrixed organization; healthcare, medtech, life sciences, or regulated-industry experience strongly preferred.
- Demonstrated experience translating policies, standards, or partially defined workflows into scalable operating models, governance processes, metrics, and execution plans.
- Experience leading cross-functional programs with stakeholders across AI/technology, business units, Legal, Privacy, Security, Regulatory, Quality, Compliance, and enterprise governance teams.
- Working knowledge of AI/ML solution delivery, data governance, Responsible AI concepts, model risk management, privacy, cybersecurity, and risk-based controls.
- Strong program management skills, including meeting facilitation, decision tracking, issue escalation, roadmap planning, executive reporting, and measurable outcome delivery.
- Strong analytical, problem-solving, and communication skills with the ability to influence without direct authority, drive alignment, and navigate ambiguity in a fast-moving environment.
Preferred qualifications:- Experience operationalizing Responsible AI, AI governance, model risk management, data governance, or technology risk programs at enterprise scale.
- Experience designing governance metrics, dashboards, compliance reporting, maturity models, or executive scorecards.
- 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 supporting AI/ML-enabled products, clinical decision support, digital health, software as a medical device (SaMD), or enterprise AI platforms in a regulated environment.
- Experience with change management, training, communications, and stakeholder enablement for enterprise processes or governance programs.
- Certification in Agile, Product Management, Project/Program Management, Risk Management, Privacy, Security, or Compliance (e.g., CSPO, SAFe, PMP, or equivalent).
- Ability to balance innovation velocity with governance rigor, making processes practical, scalable, and measurable for teams across divisions, regions, and functions.
Requisition ID: 631113Minimum Salary: $ 106800 Maximum Salary: $ 202900 The anticipated compensation listed above and the value of core and optional employee benefits offered by Boston Scientific (BSC) - see www.bscbenefitsconnect.com-will vary based on actual location of the position and other pertinent factors considered in determining actual compensation for the role. Compensation will be commensurate with demonstrable level of experience and training, pertinent education including licensure and certifications, among other relevant business or organizational needs.
At BSC, it is not typical for an individual to be hired near the bottom or top of the anticipated salary range listed above.Compensation for
non-exempt (hourly), non-sales roles may also include variable compensation from time to time (e.g., any overtime and shift differential) and annual bonus target (subject to plan eligibility and other requirements).
Compensation for
exempt, non-sales roles may also include variable compensation, i.e., annual bonus target and long-term incentives (subject to plan eligibility and other requirements).
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