Senior AI Product Manager

NeueHealth

. Identify and shape AI product opportunities through stakeholder discovery, workflow analysis, value sizing, feasibility assessment, and risk identification .

Posted 9/18/2026full-timeRemote • Florida • United StatesSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in AI Product Management, including stakeholder engagement, product requirement translation, and KPI definition. Proficient in managing product lifecycles, ensuring compliance, and driving user adoption through effective communication and training.

Highest-signal resume keywords

AI/ML ConceptsProduct Management ExperienceStakeholder ManagementData Analysis SkillsAgile Environment Adaptability

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Product Requirements DefinitionKPI DevelopmentUser Story CreationFeasibility AssessmentRisk IdentificationWorkflow AnalysisAcceptance Criteria DevelopmentEvidence-Based Decision MakingContinuous Improvement RecommendationsAmbiguous Problem Translation

Soft Skills

Strong Communication SkillsStakeholder CommunicationChange ManagementCollaborationAdaptability

Tools & Technologies

DatabricksAI SolutionsUAT SupportProduct DocumentationRoadmap Management

Industry Keywords

Healthcare ExperienceComplianceSecurityClinical OperationsProduct Lifecycle Management

About the role

Key responsibilities & impact

Identify and shape AI product opportunities through stakeholder discovery, workflow analysis, value sizing, feasibility assessment, and risk identification
Own one-pagers, PRDs, user stories, acceptance criteria, launch criteria, and KPIs for AI solutions
Partner with the Head of AI to prioritize work based on business value, user impact, strategic fit, feasibility, risk, compliance, and capacity
Maintain and communicate the roadmap or backlog for assigned AI features, workflows, products, or product areas
Make timely product decisions during implementation, including scope, requirements, tradeoffs, and outcome alignment
Verify completed solutions against product requirements, acceptance criteria, user needs, and success measures
Support UAT, workflow validation, pilot planning, launch readiness, and post-launch feedback collection
Drive adoption through stakeholder communication, rollout planning, training, user guidance, change management, and support workflows
Own post-launch KPI monitoring, user feedback analysis, bug/enhancement intake, and continuous improvement recommendations
Partner with Engineering, Compliance, Security, Legal, Clinical, and Operations to ensure AI solutions are responsible, secure, compliant, auditable, and trustworthy
Maintain product documentation, including requirements, roadmap materials, decision logs, launch plans, KPI definitions, stakeholder updates, and performance summaries
Report to the Head of AI Product & Engineering and collaborate with the Director of AI Engineering and cross-functional stakeholders
Perform other duties and responsibilities as assigned

Requirements

What you’ll need

Strong familiarity with modern AI/ML or LLM concepts
Bachelor’s degree in Business, Computer Science, or Data Science; equivalent practical experience may be considered
4+ years of product management experience across the full development lifecycle including ownership responsibility
Demonstrated ability to translate ambiguous business problems into clear product requirements, priorities, success metrics, and execution plans
Strong stakeholder management skills across business, technology, operations, clinical, compliance, and executive stakeholders
Strong data and analytical skills, including defining KPIs, interpreting data, evaluating product performance, and making evidence-based prioritization decisions
Comfortable partnering with engineering and security teams on feasibility, architecture tradeoffs, data dependencies, integration needs, implementation sequencing, testing, and launch readiness
Strong written and verbal communication skills, including creating product documents, executive summaries, roadmap materials, user guidance, and launch communications
Comfortable operating in a fast-paced, evolving agile environment with ambiguity, competing priorities, rapid learning, and a bias toward action
Hands-on experience building with AI preferred
Experience deploying solutions with embedded AI capabilities, human-in-the-loop requirements, escalation paths, review workflows, exception handling, and operational controls preferred
Experience working in healthcare preferred
Strong data fluency preferred
Code literate preferred
Databricks experience is a plus

Benefits

Comp & perks

Work-from-home position
Equal opportunity employment