A technology organization is expanding its quality engineering function to support a next-generation platform initiative. This role focuses on building and advancing automated testing capabilities with a strong emphasis on Python-based automation, data validation, microservices testing, and the practical use of AI tools to improve test effectiveness and coverage.
The automation engineer will work hands-on designing scalable automation frameworks and applying AI-assisted techniques across the testing lifecycle to support complex, distributed systems.
Responsibilities
Automation and framework development
- Design, build, and maintain modern automation frameworks.
- Develop and execute automated test suites across API, microservices, and user interface layers.
- Create reusable automation components that support scalability and long-term maintainability.
- Implement performance and functional testing using industry-standard tools.
AI-enabled testing practices
- Apply AI tools to support test case creation from requirements and technical documentation.
- Use AI-assisted approaches to identify edge cases, negative scenarios, and regression risks.
- Leverage AI to suggest automation scripts, reusable components, and optimization opportunities.
- Improve regression strategies by analyzing code changes and identifying impacted areas.
Data validation and analysis
- Perform data validation and reconciliation using SQL and Python.
- Identify data anomalies, trends, and inconsistencies through automated checks.
- Compare source and target datasets as part of system validation and testing workflows.
Microservices and cloud testing
- Validate microservices-based and distributed system architectures.
- Test APIs and service integrations in cloud environments.
- Collaborate with engineering teams to understand service interactions and integration points.
Required experience and skills
- Strong proficiency in Python.
- Strong working knowledge of SQL for data validation and analysis.
- Experience designing and maintaining test automation frameworks.
- Hands-on experience testing APIs, microservices, and distributed systems.
- Experience with modern automation and testing tools such as JMeter, PyTest, Selenium, or equivalent frameworks.
- Exposure to cloud platforms such as AWS, Azure, or GCP.
- Practical experience using AI tools to enhance:
- Test generation
- Automation development
- Regression optimization
- Data validation
Preferred experience
- Experience working with notebook-based environments used for data analysis.
- Background supporting data-intensive or analytics-driven platforms.
- Familiarity with enterprise-scale testing environments.
- Exposure to Java-based systems.
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