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Stack AI

Lead QA Engineer

RemoteUnited States only
Published
Role
QA
Experience
Lead
Employment
Full-time
Company size
Startup
Salary not disclosed
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Open to US only. Set where you work from to check your eligibility.

No BS summary

We’re looking for a QA Engineer to join our fast-moving engineering team at Stack AI in San Francisco. You’ll play a key role in ensuring the reliability, scalability, and usability of the platform that powers AI-driven workflows for thousands of users.

Core skills

PythonTypeScriptCypress/Playwright/Jest

Required skills

JavaScriptPyTest/unittestRESTGraphQLGitCI/CDGitHub Actions/RenderPostmank6

Optional skills

TemporalPostgreSQLRedisDockerFastAPI

What you'll do

  • Design, write, and execute test plans for new features across web, API, and backend systems.
  • Develop and maintain automated test suites (unit, integration, end-to-end) for a modern TypeScript + Python stack.
  • Own and extend our test automation framework (Cypress, Playwright, or similar).
  • Integrate testing into CI/CD pipelines to catch regressions early.
  • Partner with Product and Engineering to understand user workflows and identify high-risk areas.

What they require

  • 2–4 years of experience in QA, Test Automation, or Software Testing.
  • Must be proficient in Python.
  • Strong familiarity with JavaScript/TypeScript (Cypress, Playwright, or Jest) and Python-based testing frameworks (PyTest, unittest).
  • Experience testing APIs (REST/GraphQL) and web applications end-to-end.
  • Solid understanding of software lifecycles, Git, and CI/CD (GitHub Actions, Render, or similar).

Stack AI is a no-code drag-and-drop tool to quickly design, test, and deploy AI workflows that leverage Large Language Models (LLMs), such as ChatGPT, to automate any business process. Our core value is to make it extremely easy to build arbitrarily complex AI pipelines using a visual interface that allows you to connect different data sources with different AI models. Our customers use Stack AI to build applications such as: - Chatbots and Assistants: AI agents that interact with users, answer questions, and complete tasks, using your internal data and APIs. - Document Processing: apps to answer questions, summarize, and extract insights from any document, no matter how long. - Answer Questions on Databases: connect GPT-like models to databases (such as Notion, Airtable, or Postgres) and ask questions about them. - Content Creation: generate tags, summaries, and transfer styles or formats between documents and data sources.

AIStartup
Salary not disclosed