AI Quality Assurance

Experience: 4–6 Years

Location: Delhi (On site)

Job overview:

We are looking for an experienced AI Quality Assurance (QA) Engineer to ensure the quality, reliability, accuracy, and ethical compliance of AI-driven systems. The ideal candidate should have experience testing AI/ML applications, validating data and model outputs, and building effective test strategies for production-ready AI solutions.

Key Responsibilities

• Design and execute functional, performance, regression, bias, and fairness testing strategies for AI services.
• Create detailed test plans, test cases, and automated testing suites for AI/ML applications.
• Perform model validation, data quality assessment, and AI output accuracy testing.
• Conduct bias detection, fairness testing, and responsible AI compliance validation.
• Validate APIs, AI service integrations, microservices, and data pipelines.
• Track defects and issues across development, staging, and production environments.
• Collaborate with Data Scientists and ML Engineers to ensure model performance and reliability.
• Develop and execute automated testing frameworks for CI/CD environments.
• Monitor production AI systems for performance degradation, accuracy drift, and compliance issues.

Required Skills

• 4–6 years of experience in QA, preferably with AI/ML systems or data-driven platforms.
• Strong experience in functional, performance, regression, and data validation testing.
• Experience in AI model validation, bias detection, fairness testing, and AI output verification.
• Hands-on experience with Python and SQL.
• Experience with automation tools such as Selenium, pytest, TestNG, or Cypress.
• Knowledge of Jira, TestRail, Postman, and Jenkins.
• Experience in API testing, including REST APIs, GraphQL, microservices, and integration testing.
• Understanding of ETL testing, data quality testing, and data pipeline validation.
• Knowledge of load testing, stress testing, and performance monitoring.
• Familiarity with cloud environments such as AWS, Azure, or GCP.
• Understanding of NLP, Computer Vision, or other data-centric AI applications is preferred.

Educational Qualification

• B.Tech / M.Sc. in Computer Science, Data Science, or a related field.
• QA or Test Automation certification is preferred.