Cognizant is seeking an AI Assurance Quality Engineer for an entry-level growth role. You'll join a modern AI engineering environment, combining software testing, data validation, and AI evaluation to embed assurance practices early in the product lifecycle.

What You'll Do

Execute test cases to validate AI-generated outputs, checking for accuracy, relevance, hallucination, and bias indicators.
Support testing of Retrieval-Augmented Generation (RAG) workflows and prompt templates.
Perform API and data validation testing on JSON, structured datasets, and model responses.
Contribute to automated regression test scripts for AI-enabled features.
Document defects and AI quality risks to support governance evidence trails.
Participate in sprint ceremonies, test planning, and cross-functional collaboration.
Support accessibility and usability validation for AI-driven interfaces.

What We're Looking For

Strong understanding of software testing fundamentals, including functional and non-functional testing.
Good knowledge of API testing and data validation techniques.
Good proficiency in Python or JavaScript for test scripting.
Basic understanding of AI/LLM concepts and prompt-based systems.
Strong analytical skills with attention to detail when reviewing AI outputs.
Good written communication skills for documenting defects and risks.
Familiarity with Git version control workflows.
Certified in Azure AI.
A degree in Computer Science, Software Engineering, Data Science, or a related discipline, or equivalent practical experience.
Demonstrated interest in AI systems, data quality, or automation testing.

Nice to Have

Exposure to automation frameworks like Playwright or Cypress.
Understanding of Retrieval-Augmented Generation (RAG) concepts.
Familiarity with cloud environments (AWS, Azure, or GCP).
Awareness of Responsible AI principles such as bias detection, explainability, and fairness.
Experience testing data-driven or ML-enabled systems.
Understanding of CI/CD pipelines and DevOps practices.