AI/ML Engineer - Revenue Cycle Automation-Remote

Mayo Clinic•Rochester, MN

11h•Remote

About The Position

The AI/ML Engineer, a full-stack AI/ML architect for the Revenue Cycle pillar, is responsible for both agentic solutions (UiPath Maestro, LLM orchestration, agent + bot + human-in-the-loop patterns) and predictive ML solutions. This role sets the AI architecture direction for Revenue Cycle, defines reference patterns, and collaborates with delivery teams to bring solutions from prototype to production. The ideal candidate is equally comfortable designing an agentic orchestration topology and shipping a production ML model.

Requirements

Full-stack AI/ML architect for the Revenue Cycle pillar
Experience with agentic solutions (UiPath Maestro, LLM orchestration, agent + bot + human-in-the-loop patterns)
Experience with predictive ML solutions
Experience designing agentic orchestration topology
Experience shipping production ML models
Experience developing, evaluating, and productionizing ML models using Python and modern ML libraries
Familiarity with Mayo Clinic's approved cloud and data platforms
Ability to translate Revenue Cycle opportunities into AI-enabled solutions with measurable ROI
Knowledge of standards for model lifecycle management, monitoring, bias and drift evaluation, and responsible AI practice
Ability to evaluate emerging AI capabilities and guide adoption

Nice To Haves

Experience in Revenue Cycle automation

Responsibilities

Architect full-stack AI/ML solutions for Revenue Cycle, spanning agentic orchestration (UiPath Maestro, LLM agents, RPA bots, human-in-the-loop) and predictive ML.
Define reference architectures, design patterns, and guardrails for AI use in Revenue Cycle, in partnership with enterprise architecture, security, and data governance.
Lead design of high-complexity solutions such as agentic patient portal inbasket management, combining UiPath Maestro, AI agents, RPA bots, and human-in-the-loop oversight.
Develop, evaluate, and productionize ML models using Python, modern ML libraries, and Mayo Clinic's approved cloud and data platforms.
Partner with delivery leads, app analysts, and business analysts to translate Revenue Cycle opportunities into AI-enabled solutions with measurable ROI.
Establish standards for model lifecycle management, monitoring, bias and drift evaluation, and responsible AI practice aligned to Mayo Clinic policy.
Evaluate emerging AI capabilities (new LLM models, agentic frameworks, UiPath releases) and guide when and how to adopt them.
Mentor AI/ML engineers and developers across the program; contribute to enterprise AI community of practice.