AI Product Manager

About the Role

Supports delivery of the client’s priority AI use-case roadmap by partnering with Senior AI Product Managers, engineering, architecture, data, ontology, analytics, journey, clinical, operational, privacy, security, and compliance teams.

Helps translate customer, clinical, operational, and business problems into clear product requirements, user stories, acceptance criteria, delivery plans, success measures, and launch-readiness materials for AI-enabled capabilities.

Works across multiple AI use cases rather than owning a full product area independently, helping Senior AI Product Managers maintain execution discipline, issue resolution, stakeholder alignment, documentation quality, and outcome tracking.

Contributes to discovery, requirements definition, backlog management, testing coordination, adoption support, and continuous improvement for AI-enabled customer and operational experiences.

Helps ensure AI capabilities are useful, trustworthy, measurable, and operationally sustainable while supporting safe and responsible implementation across use cases.

Responsibilities

• AI Use Case Delivery Support
  • Support Senior AI Product Managers in translating priority AI use cases into product requirements, epics, user stories, acceptance criteria, dependencies, and release plans.
  • Maintain and organize product documentation, decision logs, issue lists, delivery artifacts, stakeholder inputs, and product-readiness materials across assigned use cases.
  • Coordinate with product, engineering, architecture, data, analytics, design, clinical, operational, privacy, security, and compliance stakeholders to keep delivery work moving and aligned.
  • Identify delivery risks, open questions, dependency gaps, and decision points that require escalation to Senior AI Product Managers or other leaders.
• Product Discovery & Requirements Definition
  • Participate in discovery sessions with customers, operators, clinical teams, journey leaders, and business stakeholders to understand problems, workflows, pain points, and desired outcomes.
  • Help document jobs-to-be-done, process flows, user needs, use-case hypotheses, functional requirements, non-functional requirements, and measurable success criteria.
  • Translate user and operational feedback into structured product inputs that Senior AI Product Managers can use to refine roadmaps and prioritization decisions.
  • Support market, user, competitor, and internal capability research to inform AI product decisions and identify opportunities for reuse across use cases.
• Backlog, Roadmap & Delivery Coordination
  • Support backlog grooming, sprint planning, roadmap updates, release coordination, and cross-functional status reporting for assigned AI use cases and capabilities.
  • Help ensure user stories and requirements are sufficiently clear, testable, prioritized, and aligned to customer value, implementation feasibility, and business impact.
  • Track delivery progress, milestones, blockers, risks, stakeholder feedback, and dependencies across product, engineering, data, ontology, and operational teams.
  • Prepare concise updates, decision materials, meeting notes, action trackers, and launch-readiness materials for product and stakeholder forums.
• AI Capability Definition & Responsible Product Support
  • Help define expected AI-enabled behaviors, escalation paths, human review points, usability expectations, guardrail needs, and operational considerations for assigned capabilities.
  • Partner with AI architecture, engineering, quality, data, and clinical/operational stakeholders to document how AI capabilities should operate in real-world workflows.
  • Support responsible AI implementation by ensuring product requirements consider privacy, compliance, auditability, transparency, reliability, safety, and customer trust.
  • Help connect individual use-case needs to reusable AI platform capabilities, data products, ontology assets, integration patterns, and evaluation approaches.
• Launch, Adoption & Measurement
  • Support launch planning, stakeholder readiness, operational handoffs, change-management materials, training inputs, release notes, and adoption tracking for AI-enabled capabilities.
  • Assist in defining and monitoring product metrics, usage signals, quality indicators, feedback loops, adoption measures, and operational outcomes.
  • Gather and synthesize user, stakeholder, operational, and product analytics feedback to identify opportunities for iteration and improvement.
  • Help Senior AI Product Managers ensure each use case has clear outcomes, ownership, measurement routines, and an ongoing improvement plan.
• Cross-Use-Case Coordination & Reuse
  • Work across multiple AI use cases to identify common requirements, recurring pain points, reusable patterns, and shared capability needs.
  • Help prevent duplication by documenting where similar requirements, workflows, data needs, evaluation approaches, or platform capabilities can be reused.
  • Support collaboration across AI Product Managers, Senior AI Product Managers, Data Product Managers, Ontology teams, Engineering, Architecture, Quality Engineering, Analytics, and Operations.
  • Contribute to common product templates, intake materials, documentation standards, readiness checklists, and repeatable product delivery practices for the AI use-case portfolio.

Key Success Factors

• Strong product execution skills, including the ability to turn ambiguous ideas into clear requirements, user stories, delivery plans, and success measures.
• Ability to support multiple AI use cases simultaneously while maintaining organized documentation, follow-up, decision tracking, and stakeholder alignment.
• Practical understanding of AI-enabled product development and comfort learning how AI capabilities, data, workflows, evaluation, and operational guardrails interact.
• Strong analytical skills and ability to use product metrics, user feedback, quality signals, and operational data to identify improvement opportunities.
• Excellent communication and collaboration skills across product, engineering, architecture, analytics, data, clinical, operational, security, privacy, and compliance teams.
• Comfort operating in a regulated or high-trust environment where safety, privacy, compliance, auditability, and customer trust are critical.
• High ownership, attention to detail, follow-through, and ability to keep cross-functional work organized without requiring extensive oversight.

Requirements

• Education
  • Bachelor’s degree in Business, Product Management, Engineering, Computer Science, Data Science, Healthcare Administration, or related field.
  • Equivalent combination of education and relevant experience may be considered.
• Experience
  • 4–7 years of experience in product management, digital product delivery, technology delivery, business analysis, product operations, data products, healthcare technology, or a related field.
  • Experience supporting digital products, AI-enabled capabilities, automation solutions, analytics products, customer experiences, operational workflows, or technology-enabled services.
  • Experience translating customer, business, clinical, or operational needs into product requirements, user stories, acceptance criteria, prioritization inputs, and delivery artifacts.
  • Experience working with cross-functional teams including product, engineering, design, analytics, data, operations, and business stakeholders.
  • Healthcare, life sciences, financial services, or other regulated-industry experience preferred but not required.
• Required Technical Expertise
  • Familiarity with AI-enabled product concepts, including large language models, AI agents, orchestration, retrieval, personalization, automation, evaluation, guardrails, and human-in-the-loop workflows.
  • Ability to work with technical teams to document requirements involving APIs, integrations, enterprise systems, data products, analytics, platform capabilities, and workflow automation.
  • Strong comfort using product management tools, collaboration tools, roadmaps, backlogs, user stories, release plans, and product documentation practices.
  • Ability to interpret product analytics, adoption trends, user feedback, operational metrics, quality signals, and business outcomes.
  • Strong written communication skills and ability to create concise, well-structured documentation for technical and non-technical stakeholders.

Preferred Qualifications

• Experience supporting 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, product operations, or outcome-based product management methods.
• Experience operating in healthcare, life sciences, financial services, or similarly regulated environments involving sensitive data, safety requirements, auditability, and compliance considerations.
• Experience with product analytics, experimentation, user research, stakeholder interviews, customer journey mapping, process mapping, or operational workflow analysis.
• Experience using AI tools to accelerate research, synthesis, documentation, prototyping, analysis, or product delivery tasks responsibly and effectively.