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Mid-level QA title, metro location, and broad skill requirements increase applicant competition density.
Role requires data-platform and GenAI-specific QA skills (ClickHouse, data pipelines), limiting cross-industry transferability.
Explicit 3–5 year requirement plus mandatory SQL, pytest, API, CI/CD, and GenAI QA skills make filters strict.
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Own end-to-end quality assurance for front-end and Python backend services supporting multiple enterprise tenants.
Create, manage, and execute test plans, test cases, and regression coverage including reviewing AI-generated test suites for effectiveness.
Triage and drive root cause analysis for production issues; develop QA tools and frameworks to support automated testing pipelines.
3 to 5 years of experience in QA engineering or related roles.
Strong SQL skills with PostgreSQL and an analytical database like ClickHouse.
Proficient in Python with pytest for writing, reviewing, and debugging automated tests.
Experience with API and backend testing including multi-tenancy, authentication, error paths, and end-to-end testing across front-end and back-end.
Experienced in AI-assisted quality engineering using GenAI tools for test design and review with critical analysis skills.
Comfortable working directly with founders in a fast-growing, early-stage startup environment, influencing engineering and go-to-market strategies.
Familiar with CI/CD integration (e.g., GitHub Actions) and capable of root cause analysis through reading code and stack traces.