Quality Engineer- Test Automation

If you are passionate about water and technology, Trinnex is the place for you!

Trinnex is a visionary company that is transforming the way water resources are managed and protected.

By combining cutting-edge digital technologies, such as sensor/IoT data, models, geospatial data, and AI/machine learning, we create innovative, smart, and scalable solutions that make a difference.

Whether it's optimizing water supply and demand, detecting leaks and anomalies, or enhancing water quality and resilience, Trinnex delivers value and impact to public sector clients across the country.

Trinnex is seeking a Quality Engineer with strong experience in modern test automation, cloud-based testing, and AI-assisted quality engineering, including hands-on use of AI-assisted tooling, agents, and skills.

This role is responsible for designing, developing, and maintaining automated testing across APIs, web applications, mobile applications, and performance/load testing scenarios.

The position also supports continuous improvement of QA processes, test reliability, CI/CD integration, AI-assisted QA enablement, and technical mentoring for QA team members.

Work is performed under limited supervision and requires sound judgment, cross-functional collaboration, and the ability to communicate technical information clearly to both technical and non-technical stakeholders.

• Designs, develops, and maintains automated test suites across API, web, mobile, and performance testing domains.
• Builds reusable test utilities, fixtures, and frameworks that improve reliability, reduce maintenance effort, support consistent test data, and reduce flakiness.
• Develops mobile test automation, including simulator and emulator execution, mobile authentication flows, API mocking strategies, and mobile CI/CD integration.
• Develops and applies AI-assisted tooling, agents, and skills to support test review, debugging, documentation, automation maintenance, and developer productivity.
• Supports scalable cloud-based load testing using Google Cloud Platform, Kubernetes, and related infrastructure practices.
• Analyzes requirements, test results, defects, logs, traces, and performance metrics to identify risks, root causes, business impact, and opportunities for quality improvement.