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# Validation Engineer - AI & Data

- **Company:** Radcube, Llc
- **Location:** Indianapolis, IN, United States
- **Contract:** Contract
- **Skills:** Artificial Intelligence, Business Logic, Automation of Tests, Data Validation, Extract Transform Load (ETL), Python (Programming Language), Regression Testing, SQL Databases, Pytest
- **Published:** November 12, 2026
- **Apply:** https://www.dice.com/job-detail/cd61c741-e58d-46d5-96fc-154da1650663

## About the Role

Required Technical Expertise: Data quality engineering, SQL, Python, automated testing, PyTest or equivalent frameworks, ETL and data validation, AI and LLM evaluation, ground truth testing, regression testing, and test automation.

## Description

Summary: Validate the accuracy, reliability, completeness, and consistency of business context and AI generated responses against approved business requirements and ground truth answers., * Design and implement the testing strategy for the Domain Context Model, Business Context Repository, ontology mappings, and AI response evaluation.

 * Develop representative ground truth question and answer test sets with defined expected results and tolerances, validated by data owners.
 * Build and maintain automated evaluation tests for AI responses generated through the client's Context Injection toolkit.
 * Evaluate AI responses with and without domain context to establish baseline accuracy and measure improvements.
 * Validate numeric answers, SQL and query results, business logic, aggregations, join relationships, and narrative responses.
 * Identify and classify failures, including hallucinations, stale information, incorrect schemas, faulty joins, missing business context, and persona mismatches.
 * Develop repeatable evaluation scripts, scoring rubrics, regression tests, and accuracy reporting dashboards or scorecards.
 * Verify context repository data completeness, classification consistency, access control behavior, and changes introduced through automated context updates.
 * Document test evidence, defects, remediation results, AI readiness assessments, and validation outcomes.
 * Support release readiness, weekly demonstrations, and handover of reusable evaluation frameworks and documentation.