Senior Consultant

Job Title AI Test Engineer
Role Overview
We are seeking a highly skilled AI Test Engineer to validate, test, and assure the quality of
AI/ML-based systems. The role focuses on ensuring reliability, fairness, performance, and
robustness of AI models and intelligent applications across their lifecycle.

Key Responsibilities
 Design and implement test strategies for AI/ML models, including functional, non-
functional, and ethical validation
 Validate data quality, model accuracy, and bias detection across training and
inference stages
 Develop automated test frameworks for AI pipelines, APIs, and model outputs
 Perform model validation using statistical techniques and benchmark datasets
 Conduct adversarial testing and edge-case analysis to ensure model robustness
 Validate LLM-based applications (prompt testing, hallucination detection, responsequality)
 Collaborate with Data Scientists, ML Engineers, and Product teams to ensure end-to- end quality assurance
 Ensure compliance with AI governance, regulatory, and ethical standards
 Monitor model performance in production and support continuous testing (MLOps integration)

Required Skills & Qualifications
 Bachelor’s/Master’s degree in Computer Science, Data Science, or related field
 8+ years of experience in Automation and QA/Testing, with exposure to AI/ML systems
 Strong understanding of Machine Learning concepts (supervised/unsupervised
learning, model evaluation metrics)
 Hands-on experience with Python, and testing frameworks (e.g., PyTest, Selenium, Playwright)
 Experience testing APIs, microservices, and data pipelines
 Knowledge of ML frameworks like TensorFlow, PyTorch, or Scikit-learn
 Familiarity with data validation tools (Great Expectations, Pandera)Understanding of bias, fairness, explainability, and AI risks

Preferred Skills
 Experience with LLM testing (e.g., prompt engineering, RAG validation)
 Exposure to MLOps tools (MLflow, Kubeflow, Azure ML, SageMaker)
 Knowledge of performance testing for AI systems and Automation testing
frameworks
 Familiarity with AI governance frameworks and regulatory standards
 Experience in cloud platforms (AWS, Azure, GCP)

Nice-to-Have Certifications
 AI/ML certifications (e.g., AWS ML, Google AI, Microsoft AI Engineer)
 ISTQB Advanced/Test Automation certifications