QA Developer for AI Testing Projects: Join Our Team

We are looking for a QA Engineer to join an innovative AI testing project focused on validating automated mobile workflows on Android devices. In this role, you will work with Linux-based testing environments, execute and troubleshoot Python/JSON scripts, configure device connectivity, and support end-to-end testing scenarios. You will help ensure the quality of AI-driven user experiences by analyzing test results, documenting execution flows, and collaborating closely with the engineering team.

Job Description :

• • Good hands-on Linux command execution knowledge, hands-on script executions experience in Shell
  • Good understanding of scripts written in JSON and Python
  • Good CLI (command line interface) troubleshooting knowledge.
  • Good communication skills to understand the AI usage

The Project Testing Environment setup includes below:

• Environment Provisioning: Managed an end-to-end virtual-to-physical infrastructure stack: Chromebook – > CloudTop (VDI)  ->  Linux VM – > Docker Container.
• Hardware Integration: Configured ADB and utilized Pontis integration software to establish cross-platform connectivity between the Linux cloud architecture and physical devices.
• Device Flashing & OS Deployment: Executed custom, project-specific OS flashing on target devices and successfully deployed integrated Gemini capabilities.
• Localization & App Provisioning: Maintained and configured a suite of regional mobile applications for automated workflow testing, spanning major regional apps for Deployed localized production apps across key service sector – [for ex: Indian Apps :  Ride-Hailing (Uber, Ola, Rapido), Quick-Commerce/Grocery (BigBasket, Instamart, Zepto), and Food Delivery (Zomato, Swiggy)—to validate multi-app automation pipelines.

The High-Level Testing Scope of Summary includes:

• Execution Environment: The evaluation script (written in Python and formatted in JSON) is executed within a Linux shell environment.
• Device Connectivity: The Linux machine connects directly to a Docker image hosted on a Chromebook, which manages the connection to the physical Pixel device (Mobile phone – PIXEL 10)
• Workflow Automation: The system automatically executes and automates end-to-end user workflows, such as booking a ride or placing a grocery order, directly on the Pixel phone
• Scenario Evaluation: The script evaluates workflows across diverse testing scenarios using specific prompt types, including:
• Golden (ideal/baseline scenarios)
• Underspecified (ambiguous or partial inputs)
• Positive (expected successful paths)
• Negative (error-handling and edge cases)
• Trajectory Generation: For each execution, it records a “Trajectory” – a detailed chain of thought captured via sequential, step-by-step screenshots of the entire device proces
• Reporting & Collaboration: The system automatically updates a Google Sheet by executing the Upload script with the workflow status (Success/Failure) and outputs the final Trajectory in HTML format to be shared with the engineering team