QA Engineer (Agentic AI – AWS)

Key Responsibilities

• Develop and execute test plans, test cases, and automation scripts for AI-powered applications on AWS.
• Test data pipelines (ETL/ELT, streaming, batch) for correctness, completeness, and performance.
• Validate AI/ML workflows (model training, inference, fine-tuning, and retraining pipelines).
• Perform functional, regression, integration, performance, and security testing of cloud-based applications.
• Create automated test frameworks for APIs, microservices, and AWS Lambda functions.
• Implement continuous testing practices within CI/CD pipelines.
• Collaborate with data engineers, ML engineers, and solution architects to ensure end-to-end system quality.
• Monitor production systems and validate results against expected business/AI outcomes.
• Document test results, defects, and provide feedback for process improvements.

Required Skills & Qualifications

• 3–7 years of QA/testing experience (depending on seniority level).
• Strong knowledge of manual and automated testing practices.
• Strong skills in Python/Java/JavaScript for automation.
• Experience testing cloud-native applications on AWS (S3, Lambda, Step Functions, API Gateway, ECS, DynamoDB, etc.).
• Familiarity with CI/CD pipelines (Jenkins, GitHub Actions, GitLab CI/CD, or CodePipeline).
• Understanding of data validation and data quality frameworks (Great Expectations, Deequ, etc.).

Job Types: Full-time, Permanent

Benefits:

• Flexible schedule
• Health insurance
• Provident Fund
• Work from home

Application Question(s):

• How many years of experience do you have in QA/Testing?
• Do you have experience testing cloud-native apps on AWS (S3, Lambda, API Gateway, DynamoDB, ECS)?