QA Automation Engineer

About Us

FaceEcho, by ViSignal Inc., is an AI-powered facial and health scan platform. Users take a facial scan through our mobile app, and our AI analyzes it to surface skin, wellness, and health insights — including flagging when someone should consider following up with a doctor or specialist. We operate primarily B2B, partnering with clinics, wellness providers, and health/insurance organizations who offer FaceEcho to their own users, alongside a consumer-facing mobile app available on iOS and Android. Our product is actively deployed in a clinical research study and is expanding across new partner integrations, so release quality and reliability are a top priority for us as we scale.

We're a small, fast-moving, globally distributed team. This role reports directly to our Product Manager and will work closely with our QA lead.

The Opportunity

We currently track and run our test suite manually through a traditional Google Sheets setup — approximately 498 documented test cases, covering both UI/navigation flows (roughly 82% of the suite) and live camera capture flows such as front scans, 5-angle scans, and video scans (roughly 18%). Every test is executed and marked pass/fail by hand in the sheet. This works, but it's time-consuming and doesn't scale well as we ship more features and onboard more partners.

Our ideal end goal is full UI test automation — using AI-driven testing tools (like TestMu AI, or a comparable AI-based platform) to automatically execute our UI/navigation test cases end-to-end, rather than partial scripting or a hybrid manual/automated process. We want someone who can evaluate how far that's realistically achievable with today's AI testing tools and build toward it, starting with a clearly scoped initial engagement to set up the tooling and prove out the approach, with the potential for an ongoing role maintaining and expanding the automated suite afterward.

Detailed Scope of Work

Environment setup

• Set up a cloud-based, AI-driven automated testing environment, starting with TestMu AI (formerly LambdaTest) — or propose and justify a better alternative if you find one is a stronger fit, particularly if it offers stronger full-UI-automation capability.
• Download, install, and configure our current app build (iOS and Android) within the testing platform.
• Configure device/OS coverage appropriate for our user base.

Moving off the Google Sheet toward full UI automation

• Review our existing manual test case spreadsheet (~498 cases, currently tracked and executed entirely by hand in Google Sheets) to assess which cases can be fully automated end-to-end using the AI tooling, which require adaptation, and which (if any) are impractical to automate.
• Specifically investigate and report back on how much of the UI/navigation test cases (the 82% of the suite with no live camera involved) can be driven by the AI tool automatically — this is the core of the "full UI automation" goal — versus what still needs hand-written scripts.
• Separately assess the live-camera-dependent test cases (front scan, 5-angle scan, video scan) — including whether the platform/emulator can accept a pre-recorded or virtual video feed as camera input, since this affects whether those cases can be automated at all.
• Build out an initial working set of fully automated UI tests based on these findings, prioritizing the highest-value/most time-consuming manual cases first, with the aim of eventually retiring the manual Google Sheet execution process for anything the AI tool can cover end-to-end.

Documentation & handoff

• Document the environment setup, configuration decisions, and test suite structure clearly enough that our internal QA lead can maintain and extend it independently.
• Provide a short written recommendation on what can be fully automated vs. what will still require manual testing, and how the automated suite should be tracked/reported on in place of the current Google Sheet.

Requirements

• Proven hands-on experience with mobile app test automation (Android and iOS), ideally including AI-driven/no-code or low-code UI automation tools — please be ready to share concrete examples.
• Experience with cloud-based device testing platforms (e.g., LambdaTest/TestMu AI, BrowserStack, Sauce Labs, or similar); direct TestMu AI experience is a plus but not required.
• Experience working with Flutter apps and their camera plugin behavior is a strong plus, given our app is built in Flutter and several test cases involve live camera capture.
• Comfortable working independently from written specs and existing test documentation (including making sense of an existing manual Google Sheet test tracker), with minimal day-to-day oversight.
• Clear, proactive written communication in English — you'll be sending structured progress updates, not just completing tasks silently.
• Based in Pakistan preferred (not required), given the team's existing working relationships in that time zone.

Engagement Details

• Type: Independent contractor, hourly, remote.
• Rate: $4–5/hour, depending on experience. (2-4 hours per week)
• Work structure: Work is scoped and reviewed in approximately 5-hour increments. You'll complete an increment, report progress in writing, and we'll review and approve before authorizing the next increment — this keeps oversight light while ensuring the work stays on track.
• Payment: Paid via Remitly, on a schedule aligned with approved work increments (details/frequency to be confirmed directly with the freelancer once engaged).
• Initial scope: the setup and investigation work described above. Based on how this goes, there is strong potential for an ongoing engagement maintaining and expanding the automated test suite.
• Tools/access provided: app build access, the existing manual test case Google Sheet, and relevant credentials for the testing platform will be provided once engaged.