QA Engineer

QA Engineer

Domain: Agentic AI – AWS

Positions: 1 – 2

Job Overview:

We are looking for a QA Engineer to ensure the quality and reliability of AI-powered applications running on AWS. The role involves testing data pipelines, AI/ML workflows, and cloud-native applications, while also developing automated test frameworks and supporting continuous integration.

Key Responsibilities:

1. Develop and execute test plans, test cases, and automation scripts for AI applications on AWS.
2. Test data pipelines (ETL/ELT, streaming, batch) to ensure data is correct, complete, and performs well.
3. Validate AI/ML workflows including model training, inference, fine-tuning, and retraining processes.
4. Perform functional, regression, integration, performance, and security testing of cloud applications.
5. Build automated test frameworks for APIs, microservices, and AWS Lambda functions.
6. Integrate testing into CI/CD pipelines to enable continuous testing.
7. Work closely with data engineers, ML engineers, and architects to ensure overall system quality.
8. Monitor production systems and check that results meet expected business or AI outcomes.
9. Document test results, report defects, and suggest process improvements.

Required Skills & Qualifications:

1. 3–7 years of QA or software testing experience.
2. Experience in both manual and automated testing practices.
3. Good programming skills in Python, Java, or JavaScript for automation purposes.
4. Experience testing cloud-native applications using AWS services like S3, Lambda, Step Functions, API Gateway, ECS, and DynamoDB.
5. Familiar with CI/CD tools such as Jenkins, GitHub Actions, GitLab CI/CD, or AWS CodePipeline.
6. Knowledge of data validation and quality frameworks (e.g., Great Expectations, Deequ).