QA自动化工程师

We’re looking for an experienced QA Automation Engineer to help us scale integration testing across our product portfolio. You’ll be embedded in a Python/Django engineering environment, working on black-box integration tests that cover both UI and API flows, and eventually helping us migrate select test suites from Selenium to Playwright.

What you’ll work on

• Implementing our established integration testing framework into new products
• Supporting the integration testing backlog across existing products (Selenium-based)
• Writing and maintaining Gherkin feature files and Python Behave test specs
• Running and maintaining CI pipelines via TeamCity and GitLab MRs
• Accurately mocking AWS services (localstack, moto) to isolate test environments
• Contributing to a future Playwright migration roadmap

Tech stack you’ll work with

• Language: Python (tests and applications)
• Frameworks: Django, Django REST Framework
• Test tooling: Selenium, Python Behave, Playwright (nice to have), Gherkin
• CI/CD: TeamCity, GitLab pipelines
• Infrastructure: Docker, AWS (mocking via localstack/moto)
• APIs & data: REST, SOAP, JSON
• VCS & SDLC: Git, GitLab

You’re a fit if you

• Have hands-on experience with black-box integration testing using mocks to isolate the system under test
• Have written or maintained Gherkin feature files and Behave test suites
• Are comfortable configuring GitLab pipelines for continuous testing as part of MR workflows
• Understand AWS service behavior well enough to mock it accurately in test flows
• Have worked with Docker in a testing or CI context
• Playwright experience is a plus, we’re planning a migration and want someone who can help lead it

AI-powered QA

We’re building toward an AI-augmented testing practice, and we want engineers who are already thinking that way. The ideal candidate is familiar with how AI can be applied across the QA lifecycle; from intelligent test generation and self-healing selectors, to using LLMs to analyze test failures, expand coverage from specs, and reduce maintenance overhead on flaky tests. Experience with AI-assisted tooling (Copilot, Cursor, or QA-specific tools) is a plus; what matters most is that you understand where AI adds real value in an integration testing context versus where it doesn’t.

Have hands-on experience with black-box integration testing using mocks to isolate the system under test
Have written or maintained Gherkin feature files and Behave test suites
Are comfortable configuring GitLab pipelines for continuous testing as part of MR workflows
Understand AWS service behavior well enough to mock it accurately in test flows
Have worked with Docker in a testing or CI context
Playwright experience is a plus, we’re planning a migration and want someone who can help lead it