QA Automation Engineer

FaceEcho, developed by ViSignal Inc., is an innovative AI-powered facial and health scan platform designed to provide users with detailed skin, wellness, and health insights through a mobile app. Primarily operating in the B2B space, FaceEcho partners with clinics, wellness providers, and health/insurance organizations to offer its technology, alongside a consumer-facing app available on both iOS and Android. The product is currently deployed in clinical research and expanding through new partner integrations, making release quality and reliability critical as the company scales. The team is small, fast-moving, and globally distributed, with this role reporting directly to the Product Manager and collaborating closely with the QA lead.

Key Responsibilities
- Set up a cloud-based, AI-driven automated testing environment, initially focusing on TestMu AI (formerly LambdaTest), or propose a superior alternative if justified.
- Download, install, and configure the current iOS and Android app builds within the chosen testing platform, ensuring appropriate device and OS coverage.
- Review and analyze approximately 498 existing manual test cases documented in Google Sheets, determining which can be fully automated end-to-end using AI tools, which require adaptation, and which are impractical to automate.
- Focus on automating UI/navigation test cases (about 82% of the suite) and evaluate the feasibility of automating live camera-dependent cases (front scan, 5-angle scan, video scan), including the possibility of using pre-recorded or virtual video feeds as camera input.
- Develop an initial working set of fully automated UI tests, prioritizing the highest-value and most time-consuming manual cases to eventually replace manual test execution.
- Document the environment setup, configuration choices, and test suite structure clearly to enable the internal QA lead to maintain and extend the automation independently.
- Provide a written recommendation outlining what can be fully automated versus what requires manual testing, including suggestions for tracking and reporting automated test results in place of the current manual system.

Required Qualifications
- Proven hands-on experience with mobile app test automation on both Android and iOS platforms, ideally with AI-driven, no-code, or low-code UI automation tools. Candidates should be prepared to share concrete examples of their work.
- Experience with cloud-based device testing platforms such as LambdaTest, TestMu AI, BrowserStack, Sauce Labs, or similar. Direct experience with TestMu AI is advantageous but not mandatory.
- Familiarity with Flutter apps and their camera plugin behavior is highly desirable, as the FaceEcho app is built in Flutter and several test cases involve live camera capture.
- Ability to work independently using written specifications and existing documentation, including interpreting a manual Google Sheets test tracker, with minimal day-to-day supervision.
- Strong written communication skills in English, capable of providing structured progress updates regularly.
- Preference for candidates based in Pakistan due to existing team time zone alignment, though this is not a strict requirement.

Preferred Qualifications and Benefits
- This is a remote, independent contractor role paid hourly at a rate of $4–5 per hour, depending on experience, with an expected commitment of 2–4 hours per week.
- Work is organized into approximately 5-hour increments, with progress reviewed and approved before proceeding to the next increment, allowing for light oversight while maintaining project alignment.
- Payment will be processed via Remitly on a schedule aligned with approved work increments.
- Initial engagement focuses on environment setup and feasibility investigation, with strong potential for ongoing work to maintain and expand the automated test suite based on performance.
- Access to app builds, the existing manual test case documentation, and relevant testing platform credentials will be provided upon engagement.

This opportunity is ideal for a detail-oriented automation specialist eager to pioneer AI-driven testing in a cutting-edge health technology environment and contribute to scaling a clinically significant product.