NTT DATA is seeking a skilled Quality Engineer Consultant to join our innovative team. We are committed to fostering an inclusive and adaptable environment for professionals eager to grow with us. This role offers an exciting opportunity to contribute to cutting-edge projects within a forward-thinking organization.

As a Quality Engineer Consultant, you will play a crucial role in ensuring the highest standards of software quality. Your expertise will be vital in developing and implementing comprehensive testing strategies across various platforms and applications. This position is based in Noida / Gurgaon, Delhi, India.

This role involves conducting thorough quality engineering, including software testing and the implementation of automated test solutions. You will perform database validation and data reconciliation using strong SQL skills. Responsibilities include testing APIs, microservices, web applications, data pipelines, and enterprise platforms.

Additionally, you will validate front-end workflows for React JS applications and integrate automated tests into CI/CD pipelines. A key aspect will be applying understanding of AI/ML testing concepts, such as LLM response validation, prompt regression, RAG evaluation, and agent workflow testing. You will leverage strong analytical skills to identify potential risks and failure modes in complex systems.

To excel in this position, strong experience in quality engineering, software testing, and test automation is essential. Proficiency in SQL for database validation, data reconciliation, and test data analysis is required. Experience testing APIs, microservices, web applications, data pipelines, and enterprise platforms is necessary.

Candidates should have experience testing React JS applications and validating front-end workflows. Experience integrating automated tests into CI/CD pipelines is a must. A solid understanding of AI/ML testing concepts, including LLM response validation, prompt regression, RAG evaluation, model output validation, and agent workflow testing, is crucial. Strong analytical capabilities to identify edge cases and quality risks are highly valued.