We are seeking an experienced Senior Product Manager to lead the development of innovative AI-powered patient engagement experiences within a virtual healthcare environment. In this role, you will shape how conversational AI and intelligent automation support patients and families throughout their healthcare journey, from initial inquiries and enrollment to ongoing treatment engagement. You will own the strategy, roadmap, and execution of patient-facing AI solutions across multiple channels, including chat, voice, SMS, and in-app experiences. Working closely with Clinical, Engineering, Design, Data, Operations, and Compliance teams, you will ensure that AI meaningfully improves access to care while reducing administrative complexity. You will also establish the frameworks needed to evaluate AI performance, maintain clinical safety, and deliver measurable improvements in patient outcomes. This is a hands-on strategic leadership opportunity for someone passionate about responsible AI innovation, exceptional user experiences, and making quality healthcare more accessible.
AI Product Strategy and Roadmap: Own the end-to-end strategy, development, and execution of patient-facing AI experiences, defining the product roadmap from opportunity identification and prototyping through safety assessments, phased launches, and continuous optimization.
Conversational AI Development: Personally design, build, and refine AI-powered agents across chat, voice, SMS, and in-app channels, including developing system prompts, conversation flows, guardrails, and evaluation datasets.
Patient Journey Optimization: Develop seamless automated experiences that support patients and families throughout their healthcare journey, including initial inquiries, intake, eligibility verification, scheduling, benefits and billing, care-team communications, and operational handoffs.
Responsible AI Implementation: Ensure AI solutions are introduced thoughtfully and responsibly, prioritizing patient needs, clinical quality, and meaningful outcomes rather than automation volume alone. Identify situations where human intervention is essential and ensure technology enhances rather than replaces human care.
Patient Engagement and Lifecycle Communications: Partner with behavioral insights and patient engagement teams to develop lifecycle communication strategies across engagement platforms and AI agents, progressing toward a Next Best Action model that delivers the right message through the right channel at the right time.
Behavioral Science Integration: Apply behavioral science principles, including friction reduction, timing, message framing, and habit formation, to improve conversation design, patient engagement, and treatment continuity.
Clinical Safety and Escalation: Collaborate with clinical leadership to establish safety standards for AI-powered conversations, including crisis detection, escalation protocols, appropriate communication boundaries, and reliable human handoffs for sensitive or high-risk situations.
Operational Workflow Transformation: Work with Operations teams to redesign existing processes around AI capabilities, determining which activities should be automated, which require human oversight, and how employees can review, correct, and take over AI-driven interactions.
Performance Measurement and Evaluation: Establish comprehensive evaluation frameworks covering pre-launch testing, ongoing production monitoring, and measurable success criteria. Track AI performance through patient outcomes, access to care, operational efficiency, engagement, and satisfaction.
Cross-Functional Collaboration: Partner with Clinical, Product, Engineering, Design, Data, Operations, Compliance, and Commercial teams to align priorities, resolve development challenges, and bring new AI initiatives safely into production.
Patient and Family Co-Design: Engage patients and families through advisory groups and structured feedback initiatives to test, evaluate, and improve AI-powered experiences based on real user needs.
Executive Communication: Present product vision, strategic recommendations, risk assessments, performance insights, and measurable business outcomes to executive and clinical leadership.
Vendor and Technology Management: Manage external AI technology providers and platform partners, evaluate vendor capabilities, assess build-versus-buy decisions, and identify opportunities to optimize technology costs and performance.
Continuous Improvement: Monitor real-world agent performance, analyze feedback and operational data, and continuously refine prompts, workflows, safeguards, and product experiences.
Strategic Organizational Impact: Drive key organizational objectives and contribute to the long-term vision for using AI to improve healthcare accessibility, patient engagement, and the quality of care delivery.