Job Description
QA Automation Engineer
London – 2 days in office
Up to £60,000 + benefits
An opportunity to join a fast-growing tech business where quality engineering sits at the heart of the product. This role will focus on building and scaling modern test automation within a microservices environment, using advanced tooling and AI-assisted approaches to improve reliability and delivery speed.
The Company
A well-funded, scaling technology business building a data-driven digital product. Teams work in cross-functional squads and place a strong emphasis on engineering quality, product innovation, and user experience. It’s an environment where engineers have real influence over how the product evolves.
The Role
* Build and maintain automated test suites to reduce manual testing and improve coverage.
* Work closely with engineers, product managers, and QA peers to ensure requirements are testable and clearly defined.
* Use AI-enabled tooling to accelerate test creation, debugging, and synthetic data generation.
* Plan and execute testing across smoke, regression, functional, and performance areas.
* Maintain test documentation and support best practice across the QA function.
* Contribute to Agile ceremonies and continuous improvement within the squad.
* Support the wider adoption of test automation across the engineering team.
Skills & Experience
* Commercial experience in QA automation with Java or Kotlin.
* Strong understanding of object-oriented programming principles.
* Experience testing APIs using tools such as RestAssured, Feign, Swagger, or Postman.
* UI automation experience with Selenium, Selenide, or Playwright.
* Familiarity with TestNG, JUnit, and SQL for data validation.
* Experience with debugging and monitoring tools (e.g. Sentry or Elasticsearch).
* Exposure to performance testing tools such as JMeter or Gatling.
* Experience with test management tools (e.g. TestRail) and delivery tools such as Jira and Confluence.
* Knowledge of CI/CD pipelines, ideally GitHub Actions.
* Experience working in Agile environments, ideally with microservices architectures.
* Exposure to AI tooling to improve productivity is highly beneficial.