Senior QA / SDET Engineer
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Some ghost-posting signals
- open for 40 days (30+ days starts to look stale)
- 81 open roles at this company in 30 days (mass-hiring blitz)
- no salary disclosed (correlates with ghost postings)
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About the role
What You Will Do:
The role
Automation-first quality engineering for a platform combining voice, desktop, intelligence, and AI.
We emphasize AUTOMATION — we do not do manual QA here.
Weekly code deploys are the heartbeat: when a QA branch is ready, regressions run fast, results report fast, and the train doesn't wait.
Startup environment: 1-week sprints, fail fast, move forward.
What you'll own
Automation coverage for your squads' services
Fast-turnaround regression suites gating weekly deploys ·
Rapid detection and reporting
Quality signal in minutes, not days
Load/stress coverage for your services' latency budgets
Your committed timelines.
Who you are
Self-starter with grit and a show-me mentality.
You consider yourself exceptional, love new technology, adapt fast when the stack changes under you, and use AI tools daily to multiply velocity — including AI-assisted test generation.
A team player who likes winning, and a partner to dev, not a gate: when something breaks, you help the dev team isolate it fast.
What You Will Bring:
5+ years SDET; writes real automation code (Go / Python), not manual scripts. Automation-first is a conviction, not a preference.
Master issue-isolator and root-cause debugger — you narrow a failure to the service, the commit, the event; dev teams love your bug reports because they're half the debugging done.
Fast regression discipline — parallelized suites, smart test selection, results in minutes; quality at weekly-deploy speed without becoming the bottleneck.
Comfortable in high-load testing environments — load, stress, and soak testing of high-throughput, low-latency systems; you know how to find the knee of the curve.
Experience testing event-driven systems, WebSocket flows, and browser extensions — ordering, race conditions, real-time state.
CI-native mindset — tests wired into trunk-based CI/CD; flake management as a first-class discipline (a flaky suite is a broken suite).
Contract/API testing between services; synthetic data and traffic generation (simulated calls, event streams, audio) for repeatable real-time testing.
Testing AI outputs — eval-style assertions for non-deterministic LLM/ML features — a strong plus.
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