QA Lead R2R Agentic Automation

SF_OP_208650-7 –

QA Lead – R2R Agentic Automation

Rate -70/hr

Remote / WFO / Hybrid: Remote

Hire Type (FTE/Contract): Contract

Project Duration: 5 months – most likely to extend till 12 months

Expected Start Date: 11/02/2026

Role Summary

We are seeking an experienced QA Lead to define and execute validation strategies for data pipelines, deterministic calculations, reconciliations, exceptions, AI-supported outcomes, and end-to-end financial-control scenarios within the R2R Agentic Automation program.

Key Responsibilities

• Create data and reconciliation validation strategies.

• Develop automated data-quality and reconciliation tests.

• Validate source-to-target transformations.

• Compare expected versus actual results.

• Validate enrollment-to-capitation reconciliation.

• Validate claim-to-encounter traceability and disposition.

• Test deterministic calculation and rule engines.

• Execute regression and historical-period testing.

• Validate exception classification and supporting evidence.

• Test canonical model mappings and business rules.

• Validate AI/agent outputs against deterministic evidence and expected outcomes.

• Perform SQL-based validation across Bronze, Silver, and Gold layers.

• Support UAT and defect triage.

Required Skills and Experience

• 8–12 years of relevant quality assurance and testing experience.

• Advanced SQL.

• Data warehouse and lakehouse testing.

• ETL and data-pipeline testing.

• Reconciliation testing.

• Python or test-automation experience.

• Data-quality validation.

• Source-to-target validation.

• Strong analytical skills.

Preferred Qualifications

• Databricks and PySpark.

• Healthcare or Medicaid data experience.

• 834, 820, and 837 transaction validation.

• AI/ML or GenAI testing and evaluation.

• Financial reconciliation experience.

Data Analyst and AI/ML Perspective

Testing must cover data transformations, deterministic outputs, and probabilistic agent behavior. The candidate should be able to define ground truth, acceptance thresholds, and evidence-based validation scenarios.

Ideal Candidate

A hands-on QA Lead who can combine advanced data validation, reconciliation testing, automation, and analytical thinking to verify deterministic controls and AI-supported outcomes. The candidate should be comfortable working across data layers, business rules, financial-control scenarios,