Medicaid Domain Consultant R2R Agentic Automation

We are seeking a senior Medicaid Domain Consultant to provide functional leadership for Medicaid R2R transformation, translating Medicaid business, finance, regulatory, and operational requirements into business rules, reconciliation controls, functional requirements, and guidance for Data/AI engineering teams., * Serve as the Medicaid SME across enrollment, eligibility, capitation, claims, encounters, reconciliation, and financial close.

• Define and validate business requirements, reconciliation rules, exception logic, and R2R/finance controls.
• Guide canonical data models, business rules, state-specific configurations, and acceptance criteria.
• Validate 834, 820, 837, and 835 transaction flows and related business processes.
• Translate Medicaid processes into deterministic rules and appropriate AI/agent-assisted workflows.
• Validate agent recommendations, supporting evidence, and human-in-the-loop controls.
• Lead functional workshops, process mapping, gap analysis, UAT, and business validation.
• Provide functional guidance to Data, AI, Engineering, QA, Audit, Finance, and Controller teams.
• Ensure alignment with CMS/state Medicaid requirements, HIPAA, and PHI/PII controls., + Enrollment, eligibility, member months, and rate cells
• Capitation, remittance, and revenue reconciliation
• Claims adjudication, payments, and encounters
• 834, 820, 837, and 835 transactions
• R2R close, reconciliations, exceptions, and financial controls
• CMS and state Medicaid requirements

• HIPAA and PHI/PII requirements

• Strong experience in requirements validation, business-rule definition, process mapping, reconciliation/control design, UAT, and stakeholder management.
• Working understanding of AI/agentic automation, explainability, human-in-the-loop controls, and auditability.

• 15 years of Healthcare experience with deep Medicaid Managed Care and R2R/finance expertise.
• Strong knowledge of, A senior Medicaid SME who can translate complex Medicaid and R2R requirements into clear business rules, effective controls, testable requirements, and actionable guidance for Data and AI engineering teams, ensuring solutions are accurate, compliant, explainable, and audit-ready.