Senior Manager, AI Product and Portfolio Management

Additional Location(s): US-MN-Arden Hills

Diversity - Innovation - Caring - Global Collaboration - Winning Spirit - High Performance

At Boston Scientific, we’ll give you the opportunity to harness all that’s within you by working in teams of diverse and high-performing employees, tackling some of the most important health industry challenges. With access to the latest tools, information and training, we’ll help you in advancing your skills and career. Here, you’ll be supported in progressing – whatever your ambitions.

 

About the role:
The healthcare industry is experiencing rapid digital transformation, reshaping patient experiences and expectations. At Boston Scientific, we see this evolution as a powerful opportunity to advance science through innovative, insights-driven digital solutions.

 

As the Senior Manager, AI Product and Portfolio Management, you will guide a team of AI Product Owners in delivering enterprise-level AI and Generative AI programs through agile, fast-paced execution. You will own the AI portfolio strategy and execution, ensuring alignment with Boston Scientific’s digital roadmap and long-term vision.

 

In this role, you will oversee the delivery of scalable, high-impact AI solutions, working closely with AI Engineering, Platform Managers, and cross-functional teams across the business. You’ll bring an “AI-first” mindset, helping to drive continuous innovation, accelerate development using AI to build AI, and establish best-in-class product management practices for artificial intelligence.

 

You will also act as a thought leader, staying ahead of emerging technologies, promoting ethical AI practices, and championing enterprise enablement of AI across the organization.

 

Work model, sponsorship, relocation:

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

 

Your responsibilities will include:

 

Strategic leadership

• Lead and mentor AI Product Owners and Program Managers to deliver enterprise-wide AI solutions
• Accelerate delivery by using AI to build AI—empower the team with AI-powered processes to drive efficiency and speed
• Execute on a robust AI product and portfolio roadmap aligned with enterprise digital strategy

 

AI portfolio management and value delivery

• Own the full AI portfolio lifecycle: intake, prioritization, funding, resource allocation, execution, and value realization
• Collaborate with business and technical leaders to define and report KPIs for adoption, outcomes, and financial impact
• Provide regular updates to senior leadership, ensuring strategic alignment and measurable results
• Streamline end-to-end processes to improve speed and scalability of AI product delivery

 

Cross-functional collaboration

• Act as a strategic connector across AI Engineering, Platform, Data Science, IT, Enterprise Architecture, and Business Units
• Design, implement, and evolve an AI operating model for scalable and sustainable delivery

 

Agile product operations and governance

• Champion Agile product delivery practices and AI-enabled tools for backlog management, sprint planning, and reporting
• Standardize documentation, decision-making gates, and risk management processes

 

Enterprise AI enablement

• Lead and scale enterprise-wide AI initiatives with alignment to data governance, compliance, and ethical AI standards
• Promote reusability of AI capabilities to accelerate time-to-value and reduce duplication

 

Financial and risk stewardship

• Manage fiscal planning and performance for the AI portfolio, including annual operating plan development and budget oversight

 

Thought leadership and innovation

• Stay current on emerging AI trends (e.g., LLMs, AI agents, prompt engineering) and translate insights into business opportunities

 

Technical depth and AI literacy

• Possess a solid understanding of machine learning, large language models, and emerging technologies—not to code, but to ask the right questions and make informed decisions
• Evaluate feasibility, scalability, and risks of AI solutions
• Understand data ecosystems, model lifecycle, and system architecture for sustainable AI delivery