Senior Director, Applied AI - Hybrid (Acton, MA)

Insulet Corporation•Acton, MA

6d•$280,600 - $420,850•Hybrid

About The Position

The Senior Director, Applied AI will define and lead Insulet’s enterprise AI vision, strategy, and operating model, transforming critical business priorities into scalable AI and data-driven solutions that deliver measurable outcomes. This leader will oversee a diverse portfolio spanning patient engagement, customer experience, commercial effectiveness, market access, digital, operations, and enterprise productivity, while driving AI adoption and business value at scale. The ideal candidate is a strategic enterprise leader who can influence at the executive level, shape investment priorities, and lead high-performing teams across product, data science, AI engineering, analytics, and cross-functional delivery to accelerate innovation and impact across the organization. The Senior Director, Applied AI will set the enterprise vision, strategy, and operating model for the applied AI portfolio, translating Insulet's most critical business priorities into scalable AI and data products across multiple business functions. As a senior leader within the Enterprise AI and Data organization, this role will own a multi-year portfolio spanning patient engagement, customer experience, commercial and growth effectiveness, market access, digital, operations, and enterprise productivity. The role will shape enterprise AI investment choices, establish outcome and adoption standards, and ensure applied AI capabilities move from experimentation to sustained business impact. The ideal candidate is an enterprise leader who can operate at CTO and ELT levels while leading a multi-layer, diverse organization of directors, senior managers, product leaders, data scientists, AI engineers, analytics professionals, and cross-functional delivery teams.

Requirements

Master's degree in computer science, engineering, data science, analytics, business, or a related field.
18+ years of progressive experience leading enterprise-scale data, analytics, AI, digital, or technology organizations, including significant leadership of leaders and multi-disciplinary teams.
Demonstrated experience setting multi-year enterprise strategy, owning complex portfolios and investment decisions, and delivering measurable business outcomes across multiple functions.
Strong understanding of applied AI, machine learning, generative AI, large language models, AI agents, RAG, copilots, predictive models, and workflow automation.
Demonstrated ability to influence executive stakeholders and communicate strategy, investments, value, and risk at CTO and ELT levels.

Nice To Haves

Experience in healthcare, medical devices, life sciences, diabetes care, digital health, or other regulated industries.
Experience scaling AI agents, customer service copilots, commercial recommendation engines, patient engagement intelligence, or other enterprise AI products.
Strong understanding of data governance, MDM, customer, provider, patient, and commercial data, and enterprise analytics.
Familiarity with Salesforce, ServiceNow, Genesys, AWS, Azure, Databricks, Snowflake, or similar enterprise technology ecosystems.

Responsibilities

Define and own a 5+ year enterprise applied AI vision, strategy, capability roadmap, and investment portfolio aligned with company strategy and technology modernization priorities.
Set enterprise priorities across patient engagement, customer service, sales operations, marketing effectiveness, provider engagement, market access, digital, operations, and enterprise productivity.
Translate ambiguous enterprise challenges into strategic AI opportunities, investment theses, product portfolios, experiments, MVPs, and scaled capabilities.
Present applied AI strategy, portfolio choices, investment recommendations, value realization, and risk assessments to the CTO, ELT, and senior business leaders.
Partner with Finance and business executives to establish portfolio-level value cases and outcome measures, including growth, retention, productivity, cost, service quality, and patient outcomes.
Own the end-to-end portfolio of applied AI products and capabilities across multiple business functions, from discovery and prioritization through production deployment, adoption, and lifecycle management.
Establish product operating mechanisms, decision rights, roadmaps, funding priorities, and governance across a portfolio of AI-enabled products and business capabilities.
Scale reusable applied AI capabilities, including patient adherence intelligence, next-best-action recommendations, segmentation, field effectiveness, marketing optimization, forecasting, customer service copilots, AI agents, and workflow automation.
Drive enterprise integration of AI into CRM, service platforms, field tools, dashboards, digital experiences, and business operating rhythms.
Hold leaders accountable for delivery discipline, adoption, measurable outcomes, risk management, and continuous improvement across the portfolio.
Provide executive leadership for responsible deployment of applied AI in accordance with Insulet's privacy, compliance, quality, and medical device industry expectations.
Establish portfolio governance and decision frameworks for AI use cases involving patient, provider, customer, employee, and commercial data.
Partner with Security, Privacy, Legal, Compliance, Quality, Regulatory, Data Governance, and Enterprise Architecture to assess enterprise risk and define scalable controls.
Ensure appropriate human oversight, auditability, output validation, content safety, escalation, and accountability are embedded across customer- and patient-facing AI solutions.
Build, lead, and develop a multi-layer, diverse organization of directors, senior managers, product leaders, data scientists, AI engineers, analytics professionals, and cross-functional delivery teams.
Define the applied AI operating model, organizational capabilities, talent strategy, workforce plan, and leadership structure required to scale the portfolio.
Influence enterprise business and technology strategy through partnerships with the CTO, ELT, and senior leaders across Commercial, Growth, Customer Experience, Digital, Operations, R&D, Quality, Regulatory, Finance, and Technology.
Lead enterprise change and adoption strategies that embed AI into workflows, leadership routines, capability building, and decision-making at scale.