1:00 PM - 2:00 PM
Senior Product Manager Interview
Sarah Jenkins

Location
remote, United States
Commitment
Full Time
Level
Senior (5+ years)
Owns a major area of the BSWH 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 BSWH 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.
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.
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.
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 BSWH experience standards.
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.
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 BSWH’s longer-term AI strategy.
Our competitive benefits package includes the following:
Note: Benefits may vary based upon position type and/or level.