Job Opportunities

QA Engineer - AI Accuracy & Validation Testing

We are seeking a QA Engineer to join our AI Quality Assurance team, focusing on accuracy, robustness, reliability, and ethical validation of AI/ML and Generative AI systems. This role goes beyond traditional QA and involves testing non-deterministic, data-driven, and probabilistic AI outputs.
The ideal candidate has completed QA training in Manual and Automation Testing, possesses Python knowledge, and is eager to work closely with AI/ML engineers to ensure high-quality, explainable, and trustworthy AI systems.

Key Responsibilities
AI-Specific Testing Responsibilities
• Perform accuracy, validation, and consistency testing for AI/ML and Generative AI applications
• Test non-deterministic systems where the same input may produce different outputs
• Define and validate probabilistic acceptance criteria instead of fixed expected results
• Conduct model robustness testing using noisy, edge-case, and adversarial inputs
• Identify and report hallucinations in Generative AI (LLMs, chatbots, NLP systems)
• Perform prompt testing and prompt regression testing to ensure stable AI responses after model or prompt updates
• Validate explainability and justification of AI outputs (why a model produced a specific result)
• Execute fairness, bias, and ethical testing to detect skewed, unsafe, or discriminatory AI behaviour
Manual & Automation Testing
• Design and execute manual test cases for AI workflows, edge cases, and real-world scenarios
• Validate AI outputs against datasets, expected patterns, statistical thresholds, and business rules
• Develop and maintain automation scripts using Selenium with Python for AI-driven workflows
• Automate repetitive AI accuracy, regression, and validation tests
• Perform regression testing after model retraining, fine-tuning, or data updates
Collaboration & Documentation
• Work closely with AI/ML engineers and data teams to understand models, prompts, inputs, and outputs
• Analyse incorrect or inconsistent AI responses and log high-quality, detailed defects
• Work with structured and unstructured data (text, images, datasets) for testing
• Document test results, observations, risks, and AI improvement recommendations
• Participate in Agile/Scrum ceremonies and sprint QA activities

Required Skills & Qualifications
• Completed QA training in Manual and Automation Testing
• Strong understanding of testing fundamentals, SDLC, and STLC
• Mandatory Python knowledge (academic projects or professional experience)
• Mandatory experience or training in Selenium with Python
• Ability to understand and test data-driven, logic-based, and AI-powered systems
• Strong analytical thinking and attention to detail
• Good verbal and written communication skills

Good to Have
• Basic understanding of AI/ML concepts (models, datasets, accuracy, precision, recall, etc.)
• Exposure to testing AI/ML applications, chatbots, NLP systems, LLMs, or recommendation engines
• Familiarity with PyTest or other Python-based automation frameworks
• Knowledge of test data preparation, validation, and labelling
• Familiarity with Agile/Scrum methodology
• Awareness of AI ethics, bias, and responsible AI principles

Education
Bachelor’s degree in Computer Science, IT, Engineering, Data Science, or a related field