Senior AI Product Manager

Baylor Scott & White Health•Remote,

About The Position

Owns a major area of the BSWH AI use-case roadmap and translates customer jobs-to-be-done into AI-powered experiences designed to improve customer outcomes, operational efficiency, and business value. The role leads prioritization, roadmap development, requirements definition, launch planning, and success measurement for AI-enabled capabilities across one or more customer journey areas. The Senior AI Product Manager works with Digital, Journey, Clinical, Analytics, Data, Ontology, Architecture, Engineering, Operations, and other teams to define, deliver, and continuously improve AI-powered customer experiences. The role ensures capabilities address meaningful customer problems, produce measurable outcomes, and are designed for safe, scalable, and reusable implementation. It balances customer needs, technical feasibility, operational constraints, regulatory requirements, and enterprise priorities while leveraging reusable AI platform capabilities and remaining accountable for outcomes in the assigned product area.

Requirements

Bachelor's degree in Business, Product Management, Engineering, Computer Science, Data Science, Healthcare Administration, or a related field.
8–12 years of product management experience.
Demonstrated ownership of digital products, platforms, customer experiences, or technology-enabled services with measurable business impact.
Experience managing complex cross-functional roadmaps involving product, engineering, design, analytics, data, and business stakeholders.
Experience working with AI-enabled products, machine learning systems, conversational experiences, personalization platforms, automation solutions, search experiences, recommendation systems, or decision-support technologies.
Experience translating customer and business needs into structured product requirements, prioritized roadmaps, user stories, and acceptance criteria.
Experience defining and measuring product success using KPIs, customer outcomes, business metrics, usage analytics, and qualitative customer insights.
Strong understanding of AI-enabled product development and modern AI capabilities, including where AI can and cannot reliably improve customer or operational outcomes.
Familiarity with large language models, AI agents, orchestration, retrieval, personalization, evaluation frameworks, guardrails, and human-in-the-loop workflows.
Product ownership across the full lifecycle: strategy, discovery, requirements, prioritization, delivery, launch, measurement, and optimization.
Experience working with APIs, integrations, enterprise systems, data products, analytics, and platform capabilities that support reusable product development.
Ability to collaborate effectively with engineers, architects, data and analytics teams, clinical stakeholders, and operational stakeholders.
Strong analytical skills and comfort interpreting performance data, customer metrics, adoption trends, quality signals, and product outcomes.
Ability to define product strategies that translate customer problems into measurable business and customer outcomes.
Strong product judgment and prioritization skills in environments with competing stakeholder needs, technical uncertainty, and resource constraints.
Ability to translate ambiguous customer, business, clinical, or operational needs into clear product requirements, roadmaps, and execution plans.
Strong stakeholder management and influencing skills, including aligning diverse groups without formal authority.
Ability to balance short-term delivery needs with long-term product, platform, and enterprise AI strategy.
Comfort operating in regulated or high-trust environments where safety, privacy, compliance, auditability, and customer trust are critical.

Nice To Haves

Master's degree preferred.
Healthcare, life sciences, financial services, or other regulated-industry experience.
Experience owning AI-powered customer experiences, digital assistants, conversational interfaces, recommendation systems, search experiences, workflow automation products, or decision-support capabilities.
Experience applying Jobs-to-Be-Done, customer-centered design, design thinking, agile product development, or outcome-based product management methodologies.
Familiarity with AI product evaluation approaches, including quality measurement, experimentation, benchmark definition, feedback loops, and performance optimization.
Experience launching products involving AI models, enterprise systems, APIs, cross-functional delivery teams, and operational adoption requirements.
Experience working with product analytics, experimentation frameworks, customer research, behavioral insights, and customer experience measurement.
Strong ability to influence without authority and drive alignment across business, technology, clinical, operational, and executive stakeholders.

Responsibilities

Own the product strategy, roadmap, and backlog for one or more priority AI use-case areas.
Translate customer, operational, and clinical problems into jobs-to-be-done, product requirements, delivery priorities, and measurable outcomes.
Define success metrics and KPIs for business impact, customer value, adoption, engagement, satisfaction, and operational improvement.
Identify and prioritize opportunities where AI can create differentiated customer experiences or operational advantages.
Develop business cases and prioritization frameworks that weigh strategic value, implementation complexity, risk, dependencies, and expected return.
Lead discovery to understand customer needs, stakeholder requirements, operational workflows, and pain points addressable through AI.
Ensure use cases have clear problem statements, target outcomes, success criteria, and responsible stakeholders.
Partner with journey leaders, clinical and operational subject matter experts, and analytics teams to validate proposed capabilities.
Define AI-enabled capabilities, workflows, agent behaviors, escalation paths, guardrails, and customer experiences.
Translate strategy into user stories, acceptance criteria, success metrics, and delivery priorities.
Collaborate with architecture and engineering teams on appropriate solution approaches, including orchestration, retrieval, deterministic rules, personalization, automation, or human review.
Partner with design, research, and customer experience teams to make AI interactions understandable, helpful, trustworthy, and aligned with BSWH experience standards.
Lead cross-functional collaboration across Product, Engineering, Architecture, Journey, Clinical, Analytics, Data, Ontology, Security, Privacy, Compliance, and Operations.
Manage roadmap tradeoffs involving customer experience, delivery speed, technical complexity, operational readiness, safety, compliance, and scalability.
Communicate product vision, roadmap priorities, progress, risks, launch readiness, and outcomes to leadership and stakeholders.
Support launch planning, adoption, training, stakeholder readiness, and operational handoffs.
Define expected AI behaviors, quality expectations, guardrails, and acceptance criteria with clinical, operational, technical, and AI quality stakeholders.
Partner with engineering, analytics, and AI quality teams to establish evaluation approaches, testing criteria, performance expectations, and feedback loops.
Monitor AI performance, adoption, customer and operational outcomes, and quality metrics; drive iterative improvement based on feedback, analytics, operational insights, and experimentation.
Work with AI platform, architecture, data, ontology, and engineering teams to leverage reusable enterprise AI capabilities where appropriate.
Identify reusable capabilities, patterns, and requirements; connect use-case needs to common platform capabilities, integration patterns, evaluation approaches, and governance standards.
Ensure product decisions support near-term delivery and BSWH's longer-term AI strategy.