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 precise, 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 explicit, 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