Product Manager, RCM

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About the Role

We are seeking a Product Manager with strong RCM experience and an emerging understanding of agentic AI capabilities. You will lead delivery of roadmap initiatives, manage backlogs, and help shape the next generation of RCM workflows powered by intelligent automation.

This role requires someone who is equally comfortable with traditional RCM processes and AI-enabled workflows—from eligibility and insurance discovery to prior auth, claims, and denials—while collaborating with engineering, AI/ML teams, design, and operational stakeholders.

What You Will Do

Product Strategy, AI Strategy & Roadmap Execution

• Translate RCM and AI strategy into actionable roadmaps—epics, features, and user stories with clear acceptance criteria.

• Identify opportunities for agentic AI, LLM-powered workflows, and automation across eligibility, insurance discovery, COB, prior auth (manual + ePA), claim creation, and AR management.

• Partner with AI engineering, data science, and architecture to align on model capabilities, data needs, and risk/quality expectations.

• Make trade-off decisions (accuracy vs. automation, guardrails vs. flexibility) with a focus on safe AI deployment in clinical and billing contexts.

Backlog & Delivery Ownership

• Own and prioritize feature and maintenance backlogs, including AI-driven enhancement requests and model improvement cycles.

• Collaborate with engineering to refine requirements, data flows, integrations, and feedback loops for model accuracy.

• Identify and escalate blockers quickly, especially where AI components introduce new dependencies or risks.

User-Centered Product Development

• Work with RCM users to validate both traditional workflows and AI-assisted experiences (e.g., agent suggestions, automated reasoning, summarization, next-best-action outputs).

• Drive the UX vision for hybrid workflows where humans supervise or collaborate with AI.

• Conduct UAT, including testing AI edge cases and model outputs for correctness, safety, and workflow integration.

Cross-Functional Leadership

• Collaborate with Architecture Council, AI engineering, and platform teams on scalable AI design, event pipelines, data flows, and observability.

• Partner with Customer Success, Revenue Services, Compliance, and Support to ensure AI-driven features meet HIPAA, privacy, auditability, and accuracy standards.

• Guide stakeholders through rollouts, migrations, and AI-powered workflow transformations.

RCM Workflow Expertise Enhanced by AI

• Understand end-to-end RCM processes (eligibility, discovery, COB, PA, claims, payments, denials) and define where AI can:

  • reduce manual steps

  • identify missing info

  • automate data extraction

  • suggest or perform actions (agentic behavior)

  • predict denial risk

  • summarize payer rules

  • generate next-best-actions

• Use metrics (automation %, correction rate, model precision/recall, clean claim rate) to measure AI feature success.

Required Qualifications

• Bachelor’s degree in healthcare, business, engineering, or a related field.

• 5+ years of product management experience, preferably delivering workflow-heavy or operational products.

• Strong command of Agile fundamentals; experience writing epics, user stories, acceptance criteria.

• Understanding of AI concepts such as LLMs, supervised learning, prompts, evaluation frameworks, model accuracy, guardrails, and human-in-the-loop workflows.

• Ability to collaborate with engineering and AI/ML teams on data flows, APIs, integration patterns, and model lifecycle needs.

• Strong communication and problem-solving skills with ability to simplify complex AI concepts for non-technical stakeholders.

Preferred Qualifications

• Experience in Healthcare Revenue Cycle Management or Revenue Integrity.

• Prior exposure to building AI-enabled workflows, agentic systems, or automation-heavy products.

• Familiarity with clearinghouse integrations, X12 transactions (270/271, 278, 837, 835), FHIR APIs, payer rules, or ePA networks.

• Experience working with data scientists/ML engineers on features requiring model training, prompt engineering, evaluations, or monitoring.

Core Competencies

• Execution Excellence: Can convert strategy and AI opportunities into clear, incremental delivery plans.

• AI Literacy: Understands where AI adds value vs. where deterministic rules and workflow logic are more appropriate.

• RCM Domain Expertise: Deep empathy for billing teams and their operational bottlenecks.

• Human + AI Workflow Design: Capable of designing workflows where humans supervise, validate, or collaborate with an AI agent.

• Outcome-Driven: Balances automation goals with safety, compliance, auditability, and customer experience.