Senior AI Product Manager

The Senior AI Product Manager is responsible for identifying, defining, prioritizing, launching, and continuously improving AI-enabled products and capabilities. This role focuses on high-value opportunities that advance NeueHealth’s business, clinical, operational, member, provider, and stakeholder experience objectives. The Senior AI Product Manager translates ambiguous business problems into clear product requirements, success metrics, and adoption plans to ensure launched solutions deliver measurable impact.

The Senior AI Product Manager reports to the Head of AI Product & Engineering, and works closely with the Director of AI Engineering, AI Engineers, Data, Platform, Security, Compliance, Legal, Operations, Clinical, and business stakeholders.

This is a work-from-home position. Preferred candidate locations include TX, MN, or FL, subject to business need.

Role Responsibilities

• 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 that completed solutions meet product requirements, acceptance criteria, user needs, and defined 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.
• Perform other duties and responsibilities as assigned.

Education, Training, and Professional Experience

• 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, including the ability to align business, technology, operations, clinical, compliance, and executive stakeholders.
• Strong data and analytical skills with the ability to define KPIs, interpret data, evaluate product performance, and make 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 the ability to create clear 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.

Preferred Experience

• Hands on experience building with AI
• Experience deploying solutions with embedded AI capabilities with human-in-the-loop requirements, escalation paths, review workflows, exception handling, and operational controls.
• Experience working in healthcare
• Strong data fluency, including the ability to define metrics, shape data requirements, interpret analyses, and use data to inform product decisions
• Code literate
• Databricks experience is a plus