QA Automation Engineer

We're hiring a QA Engineer to make sure Cephable works, every time, for the people who depend on it. You'll take real user scenarios (a user running an automation that drafts and sends a report, rewriting a document with local AI, or chaining actions across several apps) and turn them into automated tests that run reliably across our platforms.

This isn't a role measured by test counts or pass rates. A thousand shallow tests that pass tell us little; a handful that faithfully reproduce how a user actually works tell us a lot. We want someone who starts from the user and works backward to the automation.

Because our AI runs on-device, "cross-platform" goes beyond operating systems. The models behind our automations, content generation, and voice features behave differently across CPUs, GPUs, and NPUs from different manufacturers, so your coverage will span hardware as well as Windows, macOS, iOS, and Android.

You'll be joining a small, highly collaborative engineering team, working directly with our CEO and our Director of Engineering. This role sits at the intersection of our apps and on-device AI, with significant ownership available for someone who wants to shape how we define and measure quality across both. We are highly collaborative and see product quality as a team sport.

Your top priority is our on-device automations: the AI-driven workflows that take actions across a user's apps. These need to produce the right result, in the right app, onvarious devices.

• Explore before you automate. Do hands-on, exploratory testing of new features and new hardware to understand the real user experience, then turn what you learn into automated tests.
• Translate user journeys into automated tests. Work with product, support, and users to capture how people really use Cephable, then build end-to-end tests that reproduce those workflows faithfully.
• Automate across desktop and mobile. Build and maintain test automation for our Windows, macOS, iOS, and Android apps, plus our Web, .NET, and Unity SDKs.
• Test on-device AI across hardware. Design a coverage strategy that spans GPU, NPU, and CPU vendors and device manufacturers, and catch regressions in accuracy, latency, and resource use before users do.
• Make AI-driven behavior testable. Build repeatable fixtures and evaluation methods for on-device automations and content generation, verifying outcomes in the target apps even when model output varies. Cover voice and camera input with recorded audio and video where they trigger automations.
• Prune and prioritize. Retire flaky or low-value tests, and keep the suite focused on the scenarios that protect user outcomes.
• Report what matters. Turn test results into clear signals about user impact, and partner with engineering to diagnose and fix issues at the root.
• Champion accessibility. Test alongside assistive technologies and against accessibility standards, and help the team keep users with disabilities at the center of quality decisions.

• 3+ years in QA or test automation, with a track record of building suites that teams trust.
• Hands‑on experience automating both desktop and mobile apps.
• Strong programming skills for writing and maintaining test automation.
• Experience running tests in CI/CD pipelines and managing results across many device configurations.
• A user‑first mindset: you can explain why a test exists in terms of the person it protects, not just the code path it covers.
• Sound judgment about test value, including when to delete a test, mock a dependency, or push for a real‑device run.
• Clear written communication, especially when turning ambiguous user feedback into precise, reproducible test cases.