Ai Qa Analyst

Ensure the quality and reliability of AI-powered applications and machine learning models. Design testing strategies adapted to AI systems and their specific challenges. Validate model behavior, predictions, and business outcomes. Improve testing processes and quality standards for AI-driven products. Act as a quality advocate, helping teams deliver secure, accurate, and trustworthy AI solutions. Quality Assurance & Testing
Define and execute testing strategies tailored to AI/ML-based systems. Design, maintain, and execute manual, exploratory, functional, and non-functional test scenarios. Analyze user stories and business requirements to assess testing scope and feasibility. Estimate testing effort and identify risks associated with AI models, data quality, and business rules. Support User Acceptance Testing (UAT) activities and ensure business expectations are correctly reflected in delivered solutions.
Review test results and assess impacts on functionality, performance, and AI model behavior. Identify, document, track, and validate defects through to resolution. Produce clear test execution reports, quality assessments, and status updates. Correctness Robustness Explainability Test model behavior across edge cases and unexpected scenarios. Design and execute data validation and data quality testing procedures. Validate data pipelines and input/output consistency.
Challenge requirements, acceptance criteria, and AI assumptions to ensure measurable business value. Contribute to defining AI quality KPIs and success metrics, including: Accuracy Precision Recall Participate actively in Agile Scrum ceremonies and delivery processes. Work closely with Product Owners, Developers, Data Scientists, and Business stakeholders. Share knowledge and mentor junior QA professionals when needed. Continuously improve testing methodologies, quality frameworks, and AI validation approaches. Stay up to date with emerging trends in Artificial Intelligence, Machine Learning, and Quality Engineering.
What We're Looking For
Minimum
3 years of experience as a QA Analyst. Hands-on exposure to AI/ML concepts and environments. Understanding of: Supervised Learning Unsupervised Learning Datasets and Data Quality Experience designing and executing test strategies. Strong analytical and problem-solving skills. Experience working in Agile Scrum environments. Strong communication and documentation skills. Autonomous, proactive, and detail-oriented mindset. Experience using: Jira Xray Professional level of English. Quality Assurance
Functional Testing Exploratory Testing Regression Testing User Acceptance Testing Test Planning & Reporting Risk-Based Testing AI & Data Testing
Data Quality Testing AI Performance Assessment Quality Metrics & KPIs Bias & Fairness Testing Explainability Validation Data & APIs
SQL Data Validation Data Analysis REST APIs Postman SoapUI Test Automation
Knowledge of automation tools and frameworks such as: Playwright Selenium Katalon Scripting & Test Data
Python Test Data Preparation Automation Scripting Nice to Have
Experience testing AI-powered applications or Machine Learning products. Knowledge of model monitoring and AI governance principles. Experience with automated testing frameworks. Previous exposure to Data Science or Analytics environments.