Software Developer Engineer Test [AQ-21909]

About the role

Aquent, a global leader in talent solutions, is proud to partner with an innovative and influential organization that is at the forefront of leveraging artificial intelligence to transform its industry. This company is dedicated to building robust, reliable, and cutting-edge AI-powered applications that drive significant impact for its users and stakeholders. Join a team where your expertise will directly contribute to shaping the future of AI technology and ensuring its responsible and high-quality deployment, making a profound impact on product quality and strategic initiatives. Are you passionate about the intersection of software quality and groundbreaking artificial intelligence? We are seeking a dynamic and experienced engineer to play a critical role in ensuring the integrity, safety, and performance of our next-generation AI solutions. In this pivotal role, you will be instrumental in designing, automating, and executing advanced testing strategies for AI-powered applications, machine learning systems, intelligent agents, copilots, and generative AI solutions. You will combine your strong software quality engineering background with emerging AI validation techniques to ensure our AI systems are not only innovative but also reliable, accurate, performant, and production-ready. Your work will directly enhance user trust and enable the scalable delivery of AI-powered features, making a significant impact on our product quality and strategic initiatives.

Responsibilities

• Develop and implement comprehensive testing strategies for a diverse portfolio of AI applications, platforms, and services.
• Validate AI model outputs for critical attributes such as accuracy, consistency, reliability, and safety, ensuring high-quality user experiences.
• Design and execute a full spectrum of tests including functional, integration, end-to-end, regression, and performance testing for AI solutions.
• Create sophisticated test cases tailored for prompt-driven, agentic, and retrieval-based AI workflows.
• Validate AI guardrails, business rules, permissions, and governance controls to ensure responsible AI deployment.
• Perform adversarial, negative, and edge-case testing to proactively identify potential model failures and hallucinations.
• Build and maintain robust automated test frameworks specifically designed for AI applications, streamlining the testing process.
• Develop automated evaluation pipelines for AI responses and workflows, facilitating continuous quality assessment.
• Integrate AI testing seamlessly into CI/CD pipelines, promoting a culture of continuous quality and rapid iteration.
• Implement automated quality scoring and regression detection mechanisms to maintain