QA Engineer

Role overview This QA Engineer position focuses on catching subtle media-quality defects in a video creation and editing platform before customers encounter them. The work is remote and full-time, best suited to someone with two to four years of experience who enjoys investigating judgment-based issues, such as timing drift or audio levels, rather than relying solely on automated unit tests. The role covers the full production pipeline from recording through editing, voice generation, captions, translation, sharing, and final export.

Responsibilities - Test the end-to-end pipeline including recording, script editing, AI voiceover, captions, translation, sharing, and export to download. - Build repeatable checks for attributes that regress quietly, such as audio loudness, caption timing accuracy, and output resolution. - Verify every release across all supported languages and writing systems, treating non-English coverage as a release-blocker. - Run cross-browser and cross-screen-size verification, including the browser-based recorder extension. - Own and maintain a release checklist that stays short enough that the team actually uses it. - Reproduce customer-reported issues precisely and hand engineering a clear, fixable case. - Track bugs that escape to production and feed those insights back into an improving checklist.

Requirements - Two to four years of hands-on QA experience. - A habit of reproducing an issue exactly before filing it. - Comfort with API testing and reading server logs, not only clicking through a UI. - Scripting ability in any language, enough to convert a manual check into an automated one. - Clear bug reports covering steps, expected result, actual result, and attached artifacts. - Persistence with intermittent failures that others have stopped investigating.

Nice to have - Experience testing media, audio, or any domain where "correct" is a judgment rather than a boolean. - Familiarity with Playwright, Cypress, or comparable end-to-end test frameworks. - Experience working across languages or writing systems you do not personally read.