Utilization Management Clinical AI Reviewer

About OpenTrain

OpenTrain is the #1 platform for finding and building careers in AI training and data labeling. We help clinicians and domain experts turn real-world experience into a durable freelance portfolio of AI training work, so you can discover projects, apply quickly, and grow your track record without rebuilding proof of work on every platform.

Why AI training matters for clinicians

AI training (also called data labeling or human feedback) is the human side of building modern clinical AI: people review, correct, and rate the examples models learn from. Clinicians who contribute shape how clinical decision-support systems behave, influence patient-safety safeguards, and help ensure algorithms use appropriate clinical criteria.

• Work is 100% remote and often flexible — ideal for experienced clinicians seeking part-time, high-impact work.
• Clinical judgment directly improves AI performance for utilization management, discharge planning, and transitions-of-care workflows.

The role

As a Utilization Management Clinical AI Reviewer you will assess AI-generated clinical review outputs for accuracy and appropriateness. Your reviews will inform medical-necessity determinations, level-of-care recommendations, and care-coordination decisions while producing structured feedback used to train and improve AI systems.

• Review AI-generated utilization management and case management outputs for clinical accuracy.
• Evaluate medical-necessity decisions, care-coordination recommendations, and clinical review summaries.
• Compare AI outputs against InterQual, MCG, or Milliman criteria and payer requirements.
• Support physician advisor workflows, peer-to-peer reviews, and denial appeal assessments.
• Provide structured annotations and clinical feedback to improve training datasets.

What you'll do day-to-day

Work includes a mix of real-time (concurrent) reviews and retrospective case reviews across admission, continued stay, and level-of-care decisions. You will consider regulatory and payer compliance factors and document your determinations clearly so they can be used to refine AI behavior.

• Apply UM and case-management judgment across concurrent review, retrospective review, discharge planning, and transitions of care.
• Annotate AI outputs with structured labels and written clinical rationale for training use.
• Assess compliance with CMS Conditions of Participation, the Two-Midnight Rule, observation status, and payer-specific UM requirements.
• Collaborate with physician advisors and support peer-to-peer and denial appeal workflows as needed.

Requirements

This is a senior clinical role: candidates must bring extensive utilization management or case management leadership and active clinical licensure.

• Senior experience in utilization management, case management, or clinical review leadership required.
• Active RN licensure required; physician advisor or MD background preferred.
• Hands-on experience using InterQual, MCG, or Milliman clinical review criteria.
• Well-versed in CMS Two-Midnight Rule, observation status, and inpatient criteria.
• Experience with physician advisor programs, payer peer-to-peer review, and denial appeals.
• Excellent written and verbal English communication and careful attention to clinical documentation.
• CPUR, ACM, or CCM credential is a plus.

Helpful background

The following experiences are useful but not strictly required if core requirements are met. They help you contribute faster and more effectively to AI training projects.

• Experience working in health systems, ACOs, or value-based care utilization programs.
• Comfort evaluating and critiquing AI-generated clinical review content.
• Familiarity with UM software platforms (Allscripts or similar) and clinical workflows.

Pay, schedule, and eligibility

This is a remote, US-only contractor role with a default commitment of approximately 20 hours per week. Compensation ranges from $100 to $150 USD per hour, depending on experience and qualifications.

• Pay: $100–$150 per hour (USD).
• Time: Default ~20 hours/week; part-time contractor engagement.
• Location: Remote work for candidates based in the United States.
• Language: Strong written and verbal English required.

How it works

Apply through your OpenTrain account to be considered. Qualified candidates will be invited to onboarding and provided project guidelines, annotation tools, and examples. Your reviews and structured feedback will directly improve clinical AI behavior and help build your OpenTrain profile for future opportunities.