Sr. Product Manager, AI Products

Responsibilities

• Own product strategy, roadmap, and measurable outcomes for AI-enabled and agentic workflow capabilities across a defined product area.
• Identify high-value clinical revenue cycle workflows where AI agents, automation, decision support, or workflow orchestration can improve productivity, accuracy, quality, speed, margin, or client performance.
• Prioritize roadmap investments based on business impact, user value, model readiness, data availability, implementation complexity, risk, compliance considerations, and scalability.
• Translate clinical, operational, compliance, and client needs into clear product requirements for AI-assisted workflows.
• Ensure roadmap decisions are grounded in client value, operational leverage, model performance, risk management, and business outcomes.
• Define agentic workflow patterns, including task intake, prioritization, routing, recommendation, escalation, exception handling, audit trails, and human-in-the-loop review.
• Define product requirements for AI agents, including user goals, data inputs, model outputs, confidence thresholds, guardrails, feedback mechanisms, monitoring requirements, and success metrics.
• Drive human-in-the-loop design to ensure expert users remain appropriately engaged in review, validation, escalation, and final decision-making.
• Support product experiences that are usable, explainable, measurable, operationally safe, and trusted by users.
• Partner closely with Engineering, Data Science, Design, Analytics, and Clinical Operations to develop and scale AI-enabled product capabilities.
• Lead discovery with internal operators, clinical experts, client users, implementation teams, and commercial stakeholders to validate workflow opportunities and product priorities.
• Lead cross-functional execution across Product, Engineering, Data Science, Operations, Clinical, Compliance, Client Success, Sales, and Implementation teams.
• Make pragmatic tradeoffs between innovation, risk, usability, speed, implementation complexity, and business value.
• Provide guidance to Product Managers and product team members on AI product practices, agentic workflow design, experimentation, measurement, and responsible deployment.
• Define and monitor KPIs for AI and agentic workflow performance, including adoption, automation rate, override rate, exception rate, accuracy, productivity, quality, user trust, revenue impact, and margin improvement.
• Build feedback loops that improve AI performance over time through user input, operational outcomes, quality assurance findings, and client-specific patterns.
• Partner with Compliance, Security, Privacy, and Clinical leadership to ensure AI capabilities meet regulatory, audit, PHI, clinical safety, and client trust requirements.
• Ensure product releases include clear measurement plans, feedback loops, monitoring processes, operational readiness, and appropriate controls.
• Support automation and recommendation capabilities that improve throughput while maintaining or improving quality, compliance, and user confidence.
• Partner with go-to-market teams on positioning, client education, demos, pricing input, implementation readiness, and AI value articulation.
• Communicate AI capabilities, limitations, risks, tradeoffs, and business impact clearly to executive, technical, clinical, operational, and client-facing audiences.
• Support internal and external stakeholders in understanding how AI-enabled workflows create measurable value for Accuity, clients, and users.
• Collaborate with Client Success, Sales, and Implementation teams to ensure AI-enabled product capabilities are positioned and deployed effectively.

Qualifications

• Bachelor’s degree in business, healthcare administration, technology, analytics, product management, or a related field required.
• 5+ years of product management experience, including direct experience with AI-enabled, automation, workflow, analytics, platform, or enterprise SaaS products.
• Experience defining product requirements for AI-enabled capabilities, including workflow integration, model outputs, feedback loops, monitoring, and success metrics.
• Experience partnering with Engineering, Data Science, Design, Analytics, and domain expert teams to deliver complex product capabilities.
• Experience with enterprise workflow products, preferably in healthcare, revenue cycle, clinical documentation, coding, CDI, denials, utilization management, revenue integrity, or adjacent domains.
• Experience developing business cases, defining KPIs, and measuring product outcomes.
• Preferred experience with healthcare AI, clinical AI, RCM automation, AI copilots, agentic workflow systems, clinical NLP, document intelligence, or other AI-enabled healthcare technology.
• Strong product judgment with the ability to connect user needs, operational workflows, business outcomes, technical feasibility, and risk considerations.
• Clear, executive-level communication skills with the ability to explain complex AI, clinical, operational, and financial concepts to varied audiences.
• Strong analytical thinking, including the ability to assess workflow performance, define success metrics, evaluate tradeoffs, and use data to guide decisions.
• Sound judgment in balancing innovation, responsible AI practices, compliance, user trust, implementation readiness, and speed of delivery.
• Strong collaboration skills with the ability to align Product, Engineering, Data Science, Clinical Operations, Compliance, Client Success, Sales, and Implementation stakeholders.
• Ability to lead through ambiguity, structure complex problems, and drive clarity across cross-functional teams.
• Strong stakeholder management skills, including the ability to gather input, manage competing priorities, and influence without direct authority.
• High accountability for outcomes, execution discipline, and follow-through in a fully remote work environment.
• Adaptability and comfort operating in a fast-paced, growth-oriented, performance-driven organization with evolving priorities.
• Strong organization and prioritization skills, with the ability to manage multiple discovery, delivery, measurement, and stakeholder workstreams.
• Commitment to building trusted, explainable, user-centered AI-enabled products that support quality, productivity, compliance, and client value.