Location Remote, United States Category Technology Job Type Full Time Day Job Job Id 26019564
- 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.
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 BSWH 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 BSWH'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.
BENEFITS
Our competitive benefits package includes the following
- Immediate eligibility for health and welfare benefits
- 401(k) savings plan with dollar-for-dollar match up to 5%
- Tuition Reimbursement
- PTO accrual beginning Day 1
Note: Benefits may vary based upon position type and/or level
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.