About the Role
DoctusTech builds AI agents for value-based care organizations, covering HCC risk adjustment, coding compliance, HEDIS, and clinical documentation. This is a hands-on role. You will personally review AI outputs against medical records, quantify accuracy, build the models that measure clinical and financial impact, and give engineering accurate, evidence-backed feedback. You will be the clinical quality gate before anything ships to customers.

Key Responsibilities
Clinical QA of AI Outputs
• Review AI-generated HCC suggestions, compliance flags, and documentation outputs against source records, line by line.
• Validate each diagnosis against MEAT criteria, diagnostic status (active vs. history), and current coding guidelines.
• Build and maintain gold-standard chart sets used to test agent performance.
• Score agent outputs for precision, recall, and false positive rate, and track trends across releases.
• Identify error patterns and write clear, reproducible defect reports for engineering and data science.
• Sign off on clinical quality before releases. Risk Adjustment Analysis
• Apply CMS-HCC V28 logic, including hierarchies, interaction terms, and RAF calculation.
• Assess RADV exposure on sampled charts: unsupported HCCs, error rates, and financial impact.
• Track CMS model and rule changes and translate them into product requirements. Excel Modeling & Reporting
• Build Excel models from scratch for RAF impact, PMPM and PMPY revenue, coding accuracy, and customer ROI.
• Reconcile agent output data against claims, encounter, and chart review data.




• Produce clear accuracy and impact reports for internal teams and customers. Cross-Functional Work
• Turn clinical findings into specifications, acceptance criteria, and test cases for engineering.
• Support customer teams with clinical answers on audits, accuracy questions, and coding disputes. Required Qualifications
• Medical degree (MBBS, MD, or equivalent) or another clinical degree with deep risk adjustment experience.
• 4 to 8 years in HCC risk adjustment, medical record review, coding audit, or clinical documentation integrity.
• Strong command of CMS-HCC V28, MEAT, hierarchies, RAF calculation, and RADV standards.
• Advanced Excel: pivot tables, XLOOKUP/INDEX-MATCH, nested formulas, and building calculation models from a blank sheet.
• Hands-on experience reviewing charts and documenting coding errors with supporting evidence.
• Precise, structured written communication. Preferred Qualifications
• CRC, CPC, or CDIP certification.
• Experience testing or validating AI, NLP, or other clinical software outputs.
• Working knowledge of HEDIS measures or Medicaid risk models (CDPS).
• SQL or Python for data pulls and analysis.
• Experience at a health tech startup or risk adjustment vendor. Key Success Measures
• Measurable improvement in agent precision and recall release over release.
• Clinical errors caught before release, not by customers. Accurate, reusable Excel models for RAF and ROI that the team relies on.
• Defect reports engineering can act on without follow-up questions.

📌 Clinical QA and Risk Adjustment Lead (India)
🏢 DoctusTech
📍 India