AI Quality Assurance Engineer

Corover; Delhi; Hybrid; INR 600,000 - 900,000; Full time

Job summary

Corover is seeking a tester specialized in AI services to design and implement comprehensive testing strategies, including functional, performance, and bias testing for AI/ML government use cases.

You will create test plans, validate data quality and model outputs, and collaborate with data scientists to ensure responsible AI compliance. CSI/CD pipelines will require automated testing and thorough API validation.

Qualifications

• Experience AI/ML testing for government use cases.
• Ability to validate data quality and model outputs against requirements.
• Familiarity with governance and compliance in AI testing.

Responsibilities

• Design and execute AI testing strategies (functional, performance, bias).
• Create test plans, cases, and regression suites for AI/ML apps.
• Validate model outputs against business requirements.
• Perform fairness and bias testing for government AI.
• Maintain logs of defects across dev, staging, production environments.
• Collaborate with data scientists and ML engineers on testing protocols.
• Execute automated testing frameworks for CI/CD of AI.
• Validate API, data pipeline integrity and service integration.
• Monitor production AI systems for performance and accuracy drift.

Skills

Model validation

Bias detection

Fairness testing

AI Output verification

Responsible AI testing

Tools

Selenium

pytest

TestNG

Cypress

Jira

TestRail

Postman

Jenkins

Job description

Key Responsibilities:

1. 1. Design and execute comprehensive testing strategies for AI services including functional, performance, and bias testing
2. 2. Create detailed test plans, test cases, and regression testing suites specifically tailored for AI/ML applications and government use cases
3. 3. Perform model validation testing, data quality assessment, and Al output accuracy verification against business requirements
4. 4. Conduct fairness testing, bias detection, and ethical AI compliance validation for government AI applications
5. 5. Maintain comprehensive logs of defects, issues, and resolution tracking across development, staging, and production environments
6. 6. Collaborate with data scientists and ML engineers to establish testing protocols for model performance and reliability
7. 7. Execute automated testing frameworks for continuous integration and deployment of AI
8. 8. Validate Al service integration points, API functionality, and data pipeline integrity
9. 9. Monitor production AI systems for performance degradation, accuracy drift, and compliance violations

Technical Competencies:

1. 1. Testing: Model validation, bias detection, fairness testing, Al Output verification, and responsible AI compliance testing
2. 2. Test Automation: Selenium, pytest, TestNG, Cypress for automated testing frameworks and continuous integration
3. 3. Programming Languages: Python for test scripting, SQL for data validation, basic understanding Of R for statistical testing
4. 4. Testing Tools: Jira, TestRail, Postman for API testing, Jenkins for CI/CD testing pipelines
5. 5. Data Validation: Data quality testing, ETL testing, data pipeline validation, and database testing techniques
6. 6. Performance Testing: Load testing, stress testing, and performance monitoring for Al services and data processing systems
7. 7. Security Testing: Data privacy validation, access control testing, encryption verification, and Compliance audit support
8. 8. Cloud Testing: AWS, Azure, GCP testing environments, cloud service validation, and multi-environment testing strategies
9. 9. API Testing: REST API testing, GraphQL testing, microservices testing, and integration testing methodologies