Validation Engineer, AI & Data

RADcube; Indianapolis (IN); On-site; USD 90,000 - 125,000; Full time

Job summary

RADcube is seeking a Validation Engineer, AI & Data in Indianapolis to ensure the accuracy and reliability of AI-generated responses against approved business requirements and ground truth answers. You will design testing strategies for the Domain Context Model, repository, and ontology mappings, and build automated evaluation tests.

The role focuses on evaluating AI outputs with and without domain context, validating numeric answers, and documenting validation outcomes.

Qualifications

• Bachelor's degree in CS or related field required.
• Experience with data validation and ETL processes.
• Strong SQL and Python programming skills.

Responsibilities

• Design and implement validation strategies for the Domain Context Model and Data Repositories.
• Create ground truth Q&A sets with defined tolerances and clear results.
• Develop automated evaluation tests for AI responses using the Context Injection toolkit.
• Assess AI outputs with and without domain context to measure baseline accuracy and improvements.
• Validate numeric results, SQL queries, business logic and narratives.
• Identify failures such as hallucinations, stale data, and incorrect joins or schemas.
• Develop repeatable evaluation scripts, scoring rubrics, and dashboards for reporting.
• Verify data completeness and access controls across context updates.
• Document test evidence, defects, and remediation results.
• Support release readiness and demonstrations with reusable evaluation frameworks.

Skills

Data quality engineering

SQL

Python

Automated testing

PyTest

ETL

Data validation

AI/LLM evaluation

Ground truth testing

Regression testing

Test automation

Education

Bachelor's degree in Computer Science or related field

Job description

Indianapolis, United States | Posted on 11/11/2026

Founded in 2015, RADcube is a leading technology consulting and software development firm headquartered in Carmel, Indiana. The company specializes in transforming enterprise ideas into real-world innovations by leveraging emerging technologies such as Artificial Intelligence, Blockchain, and Cloud Computing.

With nearly a decade of industry experience, RADcube serves diverse sectors, including healthcare, finance, government, and manufacturing.

Their core service portfolio includes:

• Digital Transformation and strategy consulting.


• Custom Software Development tailored to specific business needs.


• Advanced Data Analytics and AI-driven platforms.


• Cybersecurity and risk management.

Recognized for its innovation-led culture, RADcube operates RADlabs, an R&D hub focused on high-impact solutions like Responsible AI and Intelligent Automation. The firm is committed to a human-centric approach, ensuring cutting-edge technology delivers measurable business outcomes and long-term success for global clients.

The company’s commitment to innovation has earned significant industry honors:

• 2026 TechPoint Mira Awards Finalist: Named a finalist for Tech Company of the Year, recognizing high-growth pioneers that demonstrate extraordinary leadership.


• Public Sector Excellence: Awarded the Utah NASPO Cloud & Software Solutions Contract, solidifying their role as a trusted partner for large-scale government digital initiatives and more.

Job Description

Validation Engineer, AI & Data

Location: Indianapolis, IN

Summary: Validate the accuracy, reliability, completeness, and consistency of business context and AI generated responses against approved business requirements and ground truth answers.

Responsibilities

• 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.

Requirements

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.