Senior AI Product Manager

Owns a major area of the CLIENT AI use-case roadmap and is accountable for translating customer jobs-to-be-done into AI-powered experiences that improve customer outcomes, operational efficiency, and business value. Leads prioritization, roadmap development, requirements definition, launch planning, and success measurement for AI-enabled capabilities across one or more customer journey areas. Works closely with Digital, Journey, Clinical, Analytics, Data, Ontology, Architecture, Engineering, and Operations teams to define, deliver, and continuously improve AI-powered customer experiences. Ensures AI capabilities solve meaningful customer problems, achieve measurable outcomes, and are designed for safe, scalable, and reusable implementation across CLIENT use cases. Drives alignment across stakeholders while balancing customer needs, technical feasibility, operational constraints, regulatory requirements, and enterprise priorities. Partners with AI platform and architecture teams to leverage reusable AI capabilities while maintaining accountability for customer and business outcomes within the assigned product area. ESSENTIAL FUNCTIONS OF THE ROLE Own the product strategy, roadmap, and backlog for one or more priority AI use-case areas. Translate customer, operational, and clinical problems into clear jobs-to-be-done, product requirements, delivery priorities, and measurable outcomes. Define success metrics and key performance indicators that measure business impact, customer value, adoption, engagement, satisfaction, and operational improvement. Identify, evaluate, and prioritize opportunities where AI can create differentiated customer experiences or operational advantages. Develop business cases and prioritization frameworks that balance strategic value, implementation complexity, risk, dependency management, and expected return. Customer Outcomes & Jobs-to-Be-Done Ownership Lead discovery efforts to understand customer needs, stakeholder requirements, operational workflows, and pain points that can be addressed through AI-enabled capabilities. Frame AI use cases as concrete customer jobs-to-be-done and ensure each use case has a clear problem statement, target outcome, measurable success criteria, and responsible stakeholders. Partner with customer journey leaders, clinical and operational subject matter experts, and analytics teams to validate that proposed capabilities address the right problems. Ensure product decisions stay grounded in customer value, clinical/operational integrity, and measurable business impact rather than technology novelty alone. AI Capability Definition & Experience Design Define AI-enabled product capabilities, workflows, agent behaviors, escalation paths, guardrails, and customer experiences for assigned AI use cases. Translate strategy into clear user stories, acceptance criteria, success metrics, and delivery priorities that engineering and AI teams can execute against. Collaborate with architecture and engineering teams to determine when solutions should use orchestration, retrieval, deterministic rules, personalization, automation, or human review. Partner with design, research, and customer experience teams to ensure AI-powered interactions are understandable, helpful, trustworthy, and aligned with CLIENT experience standards. Cross-Functional Delivery & Adoption Lead cross-functional collaboration across Product, Engineering, Architecture, Journey, Clinical, Analytics, Data, Ontology, Security, Privacy, Compliance, and Operations teams. Manage roadmap tradeoffs across customer experience, speed of delivery, technical complexity, operational readiness, safety, compliance, and long-term scalability. Communicate product vision, roadmap priorities, delivery progress, risks, launch readiness, and outcomes to leadership and stakeholders. Support launch planning, adoption, training, stakeholder readiness, and operational handoffs for AI-enabled capabilities. Evaluation, Measurement & Continuous Improvement Define expected AI behaviors, quality expectations, guardrails, and acceptance criteria in partnership 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 capability performance, adoption, customer outcomes, operational outcomes, and quality metrics to identify improvement opportunities. Drive iterative improvement using customer feedback, evaluation results, product analytics, operational insights, and experimentation results. Work with AI platform, architecture, data, ontology, and engineering teams to ensure assigned use cases leverage reusable enterprise AI capabilities where appropriate. Identify reusable capabilities, patterns, or requirements that should be shared across multiple AI use cases or product areas. Help prevent duplicated work by connecting use-case needs to common platform capabilities, integration patterns, evaluation approaches, and governance standards. Ensure product decisions support both near-term use-case delivery and CLIENT’s longer-term AI strategy. KEY SUCCESS FACTORS Proven ability to define product strategies that translate customer problems into measurable business and customer outcomes. Demonstrated success owning complex digital product areas with accountability for adoption, customer experience, and operational impact. Strong product judgment and prioritization skills, particularly 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 understanding of AI-enabled products and how AI capabilities can be used to improve customer journeys, operational processes, and decision support. Experience partnering with engineering, architecture, analytics, data, clinical, and operations teams to deliver complex technology-enabled solutions. Strong stakeholder management and influencing skills, including the ability to align diverse groups around common objectives without relying on formal authority. Ability to balance short-term delivery needs with long-term product, platform, and enterprise AI strategy. Comfort operating in a regulated or high-trust environment where safety, privacy, compliance, auditability, and customer trust are critical. MINIMUM REQUIREMENTS Education Bachelor’s degree in Business, Product Management, Engineering, Computer Science, Data Science, Healthcare Administration, or related field. Experience 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. Strong 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. Healthcare, life sciences, financial services, or other regulated-industry experience preferred but not required. Required Technical Expertise 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 concepts such as large language models, AI agents, orchestration, retrieval, personalization, evaluation frameworks, guardrails, and human-in-the-loop workflows. Product ownership across the full lifecycle, including 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 teams, analytics teams, clinical stakeholders, and operational stakeholders. Strong analytical skills and comfort interpreting performance data, customer metrics, adoption trends, quality signals, and product outcomes. PREFERRED QUALIFICATIONS 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 operating in healthcare, life sciences, financial services, or similarly regulated environments involving sensitive data, safety requirements, auditability, and compliance considerations. 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 #J-18808-Ljbffr