AI Test Engineers

Key Responsibilities: Design, develop, and maintain AI testing and evaluation frameworks for generative AI, predictive AI, and AI-powered developer experience (DevEx) solutions. Create and execute automated test suites that validate AI model behavior, output quality, accuracy, reliability, and performance. Develop automated evaluation pipelines that integrate with CI/CD workflows and support continuous AI quality validation. Perform functional, regression, performance, and scenario-based testing of AI-enabled applications and services. Analyze AI-generated outputs to identify defects, inconsistencies, hallucinations, bias, and performance issues. Build and maintain test datasets, benchmark scenarios, prompt libraries, and evaluation artifacts used to assess AI systems. Collaborate with software engineers, AI engineers, and platform teams to improve model quality and testing coverage. Define, measure, and report AI quality metrics such as accuracy, relevance, latency, consistency, robustness, and user satisfaction. Support root-cause analysis, troubleshooting, and validation activities for AI-related defects and incidents. Document test strategies, test results, evaluation methodologies, and recommendations for stakeholders. Contribute to AI governance and responsible AI efforts by supporting evaluation activities related to reliability, fairness, transparency, and safety. Support delivery of strategic DevEx initiatives and AI-enabled platform capabilities across the software development lifecycle.

Education: Bachelor's degree in Computer Science, Information Systems, Software Engineering, Data Science, or a related technical field.

Experience: 3+ years of experience in software testing, quality engineering, test automation, or AI/ML testing. Experience designing and executing automated test strategies for complex software applications. Experience performing data validation, test result analysis, and defect investigation. Experience using source control systems and collaborative development practices.

Technical Skills: Strong programming and scripting skills in Python. Experience building automated test frameworks and test pipelines. Experience working with APIs, automated integration testing, and CI/CD environments. Understanding of machine learning, generative AI, and large language models (LLMs). Familiarity with modern testing methodologies, quality engineering practices, and software delivery lifecycles. Knowledge of statistical analysis and evaluation techniques used to validate system performance.

Preferred Qualifications: Experience testing generative AI applications, LLM-based solutions, or Retrieval-Augmented Generation (RAG) systems. Experience with AI evaluation frameworks such as DeepEval, Ragas, LangSmith, or similar tools. Knowledge of LLM observability, monitoring, and traceability practices. Experience working with Azure AI, GitHub Copilot, OpenAI, Hugging Face, LangChain, or comparable AI platforms. Familiarity with prompt engineering, benchmark dataset creation, and AI output validation techniques. Understanding of Responsible AI principles and AI governance frameworks. Experience with performance testing, scalability testing, and reliability engineering. Experience supporting developer platforms, DevEx initiatives, or software engineering productivity tools. Experience working within enterprise or regulated technology environments.