Join EY's Global Delivery Services as a QE AI Test Engineer and be at the forefront of AI innovation. This role focuses on ensuring the quality, reliability, and performance of cutting-edge AI solutions, including Narrow AI, Generative AI, and Agentic AI systems.

You will collaborate with diverse teams to evaluate AI models, validate data, perform statistical analysis, and guarantee AI applications meet rigorous functional, performance, and business requirements. This is an exciting opportunity to apply quality engineering principles to build trustworthy and scalable AI solutions within a globally connected organization.

Key responsibilities include validating diverse AI models and systems, performing comprehensive data validation (collection, augmentation, bias assessment), and evaluating AI model outputs against defined metrics to identify defects. You will design and execute test scenarios using established testing principles, applying AI-specific techniques like pairwise, metamorphic, bias, and drift testing.

Leveraging Python-based frameworks for test automation, you will collaborate with cross-functional teams to resolve quality issues throughout the development lifecycle. Support for Large Language Models (LLMs) and Agentic AI systems is also a core part of the role, alongside contributing to process improvements and working within Agile frameworks to deliver high-quality AI solutions.

To succeed in this role, you should possess proven experience in testing AI models and systems, coupled with a strong understanding of software testing principles and quality engineering practices. Foundational knowledge of AI/ML concepts, algorithms, and model validation techniques is essential.

Familiarity with Large Language Models (LLMs), Generative AI, and Agentic AI systems is required, along with experience in AI testing techniques and proficiency in Python for test development and automation. Experience with test automation tools like Selenium, Playwright, or PyTest, and knowledge of cloud platforms (Azure, AWS, GCP) are highly valued. Exposure to AI-assisted development tools such as GitHub Copilot is also beneficial. Strong analytical, problem-solving, communication, and stakeholder management skills are crucial for effective collaboration within Agile teams.