Quality Assurance Automation Engineer
Christopher AliChristopher Ali have partnered with a SaaS and bespoke development company whose products have powerful sustainability benefits. They are growing their team and are looking for an experienced QA Automation Engineer who can help them design, implement and maintain comprehensive automated test suites to ensure quality at scale. Role Purpose: To design, implement, and scale comprehensive automated test suites that ensure a complex SaaS platform meets the highest standards of quality, reliability, performance, and security. Operating as part of a UK-based, remote-first team, this role embeds test automation directly at the centre of our development lifecycle—shifting quality control left into our CI/CD pipelines, driving continuous improvement, and leveraging modern AI-assisted workflows. The role will be fully remote - work-life balance is crucial and they support a healthy blend, however you must have the right to work in the UK and sponsorship cannot be provided. Experience needed:
- 3+ years in a QA role or similar in a professional environment
- Working in an agile development cycle
- Proven experience ‘shifting testing left' by integrating automated tests into CI/CD pipelines and making test automation a core part of the development workflow
- Knowledge of performance testing tools (e.g., JMeter, k6, Locust) and load testing strategies
- Knowledge of utilising AI/LLM tooling Technical Skills Needed:
- Test Automation Frameworks: 4+ years of experience building and maintaining automated test frameworks using tools such as Playwright, Cypress, Capybara, or Selenium.
- Programming Proficiency: Strong coding skills in languages used for test automation (Ruby, JavaScript/TypeScript, or Python).
- API & Database Validation: Hands-on experience with API testing tools/frameworks and writing SQL queries (e.g., PostgreSQL) to validate test data state.
- CI/CD Pipelines: Proven hands-on experience embedding automated test suites into CI/CD pipelines (e.g., GitHub Actions, GitLab CI, CircleCI, Jenkins).
- Performance & Load Testing: Practical knowledge of performance testing tools and load testing strategies (e.g., k6, Locust, JMeter).
- AI/LLM Testing Tools: Practical experience using AI/LLM tools (e.g., GitHub Copilot, ChatGPT, Claude) to assist with test script generation, data generation, and refactoring.
- Architecture & Patterns: Understanding of scalable test design patterns, Page Object Models (POM), and test data management strategies.
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