Inpatient Medical Coding AI Training Specialist

OpenTrain AI, Inc.

United States

Remote

USD 69,000 - 96,000

Part time

5 hours ago
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Job summary

OpenTrain AI, Inc. is seeking an Inpatient Medical Coding AI Training Specialist for a remote US contract. You will review inpatient medical records and AI-generated content to ensure ICD-10-CM and ICD-10-PCS coding accuracy, applying DRG assignment rules and POA indicators.

This role emphasizes accuracy, documentation improvement, and collaboration with AI systems. The position is part-time, requires between 10 and 20 hours per week, and pays $50–$70 per hour.

Qualifications

  • Current inpatient ICD-10-CM and ICD-10-PCS coding experience.
  • Active CIC, CCS, RHIA, RHIT, or AHIMA/AAPC credential preferred.

Responsibilities

  • Review inpatient records for accurate coding under current guidelines.
  • Determine principal and secondary diagnoses for complete admissions.
  • Assess MCCs, CCs, procedures, and POA concepts effects on DRG assignment.
  • Review documentation for accuracy and flag opportunities for provider queries.
  • Evaluate AI-generated clinical notes, summaries, patient information, and code suggestions.
  • Resolve diagnosis and procedure coding discrepancies.
  • Enter and validate AI-generated patient information in inpatient medical record and encoder systems.

Skills

Inpatient coding
ICD-10-CM
ICD-10-PCS
DRG concepts
POA indicators

Job description

Inpatient Medical Coding AI Training Specialist

Review inpatient records, coding decisions, and AI-generated clinical content against ICD-10-CM, ICD-10-PCS, and inpatient standards. This remote U.S. contractor role pays $50 to $70 per hour and expects 10 to less than 20 hours per week.

Remote Hourly $50–$70/hr

$50–$70/hr

Compensation

Contract, part-time

Engagement

Remote

Location

Oct 21, 2026

Posted

Open to applicants in

United States

The Work

You will review inpatient medical records and clinical documentation while helping improve the accuracy of AI systems. The work combines medical coding judgment with structured evaluation of AI-generated content.

You will assess clinical notes, summaries, patient information, and code suggestions against real-world documentation and inpatient coding standards.

  • Review inpatient records for accurate ICD-10-CM and ICD-10-PCS coding under current guidelines.
  • Determine principal and secondary diagnoses for complete admissions.
  • Assess how MCCs, CCs, procedures, and POA concepts affect DRG assignment.
  • Review documentation for accuracy and completeness and flag opportunities for provider queries.
  • Evaluate AI-generated clinical notes, summaries, patient information, and code suggestions.
  • Resolve diagnosis and procedure coding discrepancies.
  • Enter and validate AI-generated patient information in inpatient medical record and encoder systems.
What It Pays and Takes

This is a remote contractor role for candidates located in the United States. The listed time requirement is less than 20 hours per week, with at least 10 hours per week expected.

  • Pay: $50 to $70 per hour.
  • Location: United States.
  • Schedule: Part time, with at least 10 hours per week and less than 20 hours per week listed.
  • Preferred credentials: Active CIC, CCS, RHIA, RHIT, or another AHIMA or AAPC coding credential.
  • Experience: Current inpatient ICD-10-CM and ICD-10-PCS coding experience.
  • Knowledge: DRG assignment, MCC and CC concepts, POA indicators, official ICD-10 code sets, current guidelines, and AHA Coding Clinic.
  • Additional experience: Clinical documentation review, inpatient coding, clinical documentation improvement, or a closely related field.
  • Systems: Familiarity with inpatient medical record or encoder systems.
About AI Training Work

AI training work is the human side of building artificial intelligence. People review examples, documents, and model responses so AI systems can become more accurate, and specialist work can use professional knowledge such as inpatient medical coding.

Requirements
  • Experience: Mid-Senior level
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