QA Engineer

Hiring — QA Engineer (PC Live-Streaming Studio) Drafted: 2026-08-07 A brand-new project, looking for a QA who can independently own PC-side testing. Early on I will provide support to help you get familiar with the environment, process, and business; once ramped up, you will be expected to independently own the full release-testing cycle for this project's PC side. I. What this role does day-to-day · End-to-end testing of every release's PC-side core features: the full pipeline of live audio/video capture, encoding, streaming, recording, and presentation quality · Cross-OS and cross-device (camera / microphone / external capture devices, etc.) compatibility and stability testing · Diagnosing issues along the pipeline — using logs, API responses, and media-pipeline data to localize backend / pipeline problems · Proactive coordination across teams (BE / FE / DevOps / upstream services) on test prerequisites, deployment, and release readiness · Producing structured deliverables: test cases / validation reports / bug docs / evidence (screenshots, screen recordings, network & pipeline logs) · Actively auditing cross-service version dependencies, cross-environment deployment consistency, and release blockers Note: This is a PC-focused but comprehensive role. The primary battleground is the PC side, while the project also has parts that interact with the Web and mobile App ends. You will need adequate Web / App testing ability to help run cross-end flows end-to-end. II. Baseline technical requirements We don't expect mastery of everything — just enough to operate without friction. Items marked "focus" are the focus of this role: · PC live / audio-video (focus) At least 2+ years of focused testing experience in one of: live streaming / video / real-time audio-video / client-side media applications; comfortable reasoning about the "capture - encode - stream - record - present" pipeline. · Devices & compatibility (focus) Experience with cross-OS and cross-device compatibility testing; understands how device and hardware differences affect audio/video behavior. · Performance & stability (focus) Able to test and localize PC-side CPU / GPU / memory / frame rate / thermals / poor-network adaptation, plus long-running stability issues. · Pipeline diagnosis & debugging Able to infer backend / pipeline state from API responses, logs, and media-pipeline data, and localize the problem; comfortable with common debugging tools. · Cross-end (adequate) Adequate Web / mobile App testing ability, able to support cross-end verification. · Infrastructure Comfortable with Mongo / Redis commands; able to write KQL queries in Elastic / Kibana. · CI/CD Has worked through full deploy pipelines; able to coordinate deployment / rollback with DevOps. · Language Mandarin Chinese — spoken and written. Day-to-day technical documents (Pre-QA handoff, dev specs, internal discussions) are primarily in Chinese. III. Soft skill requirements (core, ordered by importance) 1. Can independently own the full "requirement - testing - release" cycle At least 1+ year of experience owning complete release cycles, with a solid grasp of the standard QA process: requirement review / pre-test entry criteria / case review / regression / release readiness / post-release monitoring. 2. Precision in bug triage — knowing that "an issue is not a bug" Before filing a bug, the candidate proactively gathers evidence to demonstrate ~90% confidence that it is in fact a bug: · Screenshots and screen recordings are baseline, not the goal · For non-reliably-reproducible issues, the key skill is identifying the minimal-path repro steps — this is what we actually look for · Knows the typical diagnostic axes (OS / device model / network condition / cache / hardware differences / upstream service versions, etc.) · Does not file "environment flakiness" or "my own non-standard operation" as bugs 3. Treats PRDs as objects to be tested A product spec itself is something a QA must "test": · Understanding the business logic is the baseline, not the goal · Proactively surfaces gaps in the PRD: logical holes / edge cases not considered / incorrect premises / implicit assumptions · Raises boundary / failure-path / cross-module conflict concerns during requirement review, not after dev implementation 4. Multi-dimensional test case design Combines "business module x dev implementation x test methodology" to design cases covering at minimum: · UI checks (visual + interactive) · Cross-OS / device / environment compatibility · API logic verification (including failure paths) · Data-layer verification (DB state / cache consistency / local state persistence) · User-perspective scenario & flow tests (background / foreground / interruptions / poor network) · Cross-end flow tests (PC to Web to App) · Money-safety / information-security focused cases · Performance / capacity cases (CPU / GPU / frame rate / memory / thermals) · Cross-environment / cross-service version dependency audits 5. Multi-party coordination · When blocked, knows who to ping (not indiscriminate @-everyone) · In multi-party negotiations, can hold the QA position while proposing options acceptable and actionable to all sides · Primary goal is steady progress toward release, not "find the most bugs" or "block the release" 6. AI-augmented working style (a must, not a nice-to-have) · BE / FE / DevOps / QA across this project already operate in AI-augmented mode; significant daily work happens inside AI tools · The candidate must accept AI as a daily working partner · The candidate must actively use AI to amplify their own output: drafting docs / code review / debugging / evidence consolidation / knowledge sedimentation · Comfortable exposing their working process to AI; able to collaborate with AI to produce higher-quality output than working solo · Has judgment about the boundary of what to expose to AI (what is appropriate, what is not) IV. Additional expectations specific to this team Shaped by the working style of this project's lead, we especially emphasize the two points below. A. Weave AI through the whole testing workflow, at the level of industry best practice Not just "able to use" AI, but able to match the industry best practices for how QA applies AI — systematically using AI to raise test coverage, efficiency, and quality: · Integrates AI across every stage, from case design and defect analysis to regression and evidence consolidation · Can build and maintain their own automation / agents, offloading repetitive work and turning AI into a lever that amplifies their own output · Has judgment about AI's capability boundaries — knows which stages to accelerate with AI and which must be gated by a human B. Sensitive to "quality as the user actually perceives it" This is a live-streaming tool, and many things can't be signed off with a simple "pass / fail" — they require human judgment about whether what the user sees / hears is actually good: · Can make subjective A/B comparisons of picture, audio, and presentation quality, and articulate "which is better, and why" · Can spot the "the feature is correct, but the experience is bad" class of problems · Can translate subjective impressions into actionable quality feedback, rather than just "it looks off" V. Timezone requirement This project's lead and part of the dev team are in the US Eastern timezone, so real-time communication and alignment are needed. · Ideal: full-time coverage of US Eastern working hours · Minimum: at least half a US-Eastern workday of overlap each day, ensuring a stable real-time communication window with the lead and the US-Eastern devs VI. Nice-to-haves (not required) · Hands-on testing experience with live / audio-video pipelines (WebRTC / RTMP / HLS / VTT, etc.) · Familiarity with streaming / capture tools like OBS, or experience testing virtual cameras / capture devices · Exposure to testing external dependencies like LiveKit / Mux / PubNub · Web / mobile App testing experience, able to cover cross-end integration · A track record of producing structured retrospective docs · History of driving cross-team protocol improvements (e.g. surfacing cross-service dependency blind spots, advocating for an upstream hotfix split, etc.) · Prior experience as staff / tech-lead QA VII. What it will look like working together · You will independently own this project's testing: independently designing test cases, sequencing the test effort, and gating each release · Early on I will provide support — helping you get familiar with the environment, process, and business, always available to answer questions and see you smoothly ramped up. The ramp period is also a window for both sides to evaluate the fit · Testing periods involve high-density cross-team communication — you will interact directly with BE / FE / DevOps / Product / upstream service teams · Most daily work is conducted with AI collaboration: doc drafting / code review / test case design / automation