Healthcare Operations AI Trainer

When AI gets the details wrong in your field, real people pay for it. The people who know the work best have to be the ones training these models. You’re not being replaced by AI. You’re making sure it’s used accurately and safely.

• Design challenging, realistic healthcare operations scenarios based on day-to-day professional practice, including prompts and supporting de-identified or constructed files such as encounter documentation, claim forms, remittance advice, payer policies, and correspondence.
• Run healthcare operations tasks through frontier AI models and evaluate outputs such as code sets, denial appeals, clinical documentation queries, prior authorization determinations, and claims audit reports.
• Compare model outputs produced from identical prompts and files, determine which response performs better, and document strengths and shortcomings.
• Develop detailed grading rubrics defining the required elements of a correct deliverable, including coding specificity, sequencing, guideline citations, and payer-policy application.
• Identify and document concrete model failures, including unsupported codes, incorrect sequencing, missed or fabricated guideline references, ignored payer policies, and inaccurate interpretations of the request.
• Contribute expertise across coding, CDI, revenue cycle, utilization review, and payer operations, and review or refine tasks created by other domain experts.
• Propose, build, and iterate on healthcare operations tasks based on expert-review feedback.

• 2+ years of hands‑on experience preferred in medical coding and billing, revenue cycle, health information management, clinical documentation integrity, utilization review and case management, or payer operations.
• Depth of experience in at least one area: inpatient or outpatient coding, professional‑fee coding, coding audit and compliance, CDI, denials and appeals, prior authorization and utilization review, claims examination, provider credentialing and network operations, or practice or revenue cycle management.
• Working understanding of adjacent healthcare operations workflows and the ability to assess work outside a primary specialization.
• Fluency in relevant code sets and rules, such as ICD-10-CM, ICD-10-PCS, CPT, HCPCS, DRG or APC logic, payer policy, and NCCI edits, with the ability to cite applicable guidelines.
• Bachelor's degree in progress or higher, or an equivalent coding or HIM credential such as CPC, CCS, CCA, RHIA, RHIT, CDIP, or CCDS; credentials are preferred but not required.
• Current or recent individual-contributor practitioner experience; candidates whose experience is solely managerial are not the target profile.
• Professional or native-level written and spoken English, with the ability to explain complex professional reasoning clearly and concisely.
• Strong attention to detail, comfort with ambiguity, and the ability to verify documentation, numbers, sources, and facts.
• Ability to interpret feedback independently, research answers when needed, and ramp quickly on unfamiliar work from written instructions.
• General familiarity with AI and LLM tools such as Claude or ChatGPT, including the judgment to distinguish well‑reasoned responses from plausible but incorrect ones.
• Comfort with cloud file tools, browser profiles, desktop‑app installation, and everyday file handling such as spreadsheet conversion and file compression.
• Availability for at least 10 hours per week.

• Pay range of $40 to $125 USD per hour, paid via Pay Pal on a regular cadence.
• Fully remote contract work with flexible scheduling.
• Minimum commitment of 10 hours per week with no weekly maximum; full‑time hours may be available.
• Multi‑day task timers that allow work to be distributed across several days.
• Project access to Claude and ChatGPT; no personal subscription is required.
• Paid work for completed and accepted project stages, with feedback and revision as part of the process.
• Structured onboarding, training materials, dedicated Slack support, office hours, and expert review feedback.
• Opportunity to apply real‑world healthcare operations expertise to improve frontier AI systems.