• Define and deliver AI-powered RCM capabilities, including policy extraction agents, claim scrubbers, denial risk models, and intelligent automation workflows • Translate billing and payer policy complexity into structured logic suitable for AI models and rule engines • Collaborate with AI/ML engineers to define model inputs, outputs, evaluation criteria, and success metrics • Contribute to prompt engineering for LLM-based workflows, ensuring structured, testable, and reliable outputs aligned with billing accuracy standards • Participate in model evaluation, output validation, and iterative refinement to improve precision, recall, and operational trust • Use SQL and data analysis to identify trends in denials, scrub failures, payer policies, and operational inefficiencies • Support data orchestration efforts by defining required datasets, feature inputs, and transformation logic • Analyze automation performance using measurable KPIs (e.g., denial reduction, touch-time savings, automation rates) • Partner with engineering on experimentation frameworks and structured model testing • Convert high-level business problems into detailed epics and user stories with clear acceptance criteria • Create flow maps and workflow diagrams to communicate business logic, automation rules, and agent behavior • Break down AI and automation initiatives into incremental, deliverable features aligned with PI objectives • Ensure requirements address edge cases, data dependencies, and workflow impacts across enterprise and RCM users • Participate in SAFe Agile ceremonies, including backlog refinement, sprint planning, and stand-ups • Own JIRA epics and stories from concept through release • Triage and prioritize bugs, especially those related to AI output accuracy and automation reliability • Perform functional validation and assist in model output certification before release • Partner with Product Launch, Training, Support, Implementation, and RCM Operations to ensure successful feature rollout • Manage alpha and beta programs, gathering structured feedback to improve AI performance and usability • Act as a change agent promoting intelligent automation and measurable efficiency improvements across customer workflows