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Tech Stack
Tools & technologiesAWSCloudCypressJavaJenkinsMicroservicesPythonSDLCTypeScript
About the role
Key responsibilities & impact- Lead complex, often ambiguous quality work across teams. Discovery, risk analysis, test design, automation strategy, exploratory passes, and the production signal that tells you whether you got it right. You're not the squad's tester; you're the person who makes the squad better at being its own tester.
- Shape quality approaches that squads can adopt. What gets unit tested, what gets API tested, what gets UI tested, what gets exploratory time, what gets watched in production. You coach squads through those calls and harvest what works so other teams can pick it up.
- Identify tooling gaps and close them. Where teams keep tripping over the same problem (missing test data, slow feedback, unreliable environments, no good way to test a new kind of feature), you spot it, frame the work, and either lead it or hand it off in a state someone else can run with.
- Partner with Product and Design. Run 3 Amigos and Example Mapping. Translate user needs into well-defined acceptance criteria. Call quality and risk trade-offs early. Keep the roadmap honest about what's feasible to ship with confidence.
- Raise the bar on the team around you, and beyond. Thoughtful code and test review, pairing where it helps, mentoring mid-level and junior QEs and developers. The kind of "shows the team what good looks like" presence that compounds over time and gets noticed across squads beyond your own.
- Own automation strategy and CI/CD signal. Where tests run, how fast they run, how reliable they are, what they're telling us, what we do when they fail. Flakiness and noise are problems you fix rather than work around.
- Champion continuous quality. Shift left through workshop facilitation and specification refinement; shift right through production data, escaped-defect analysis, and feedback loops that change what we test next.
- Use AI to raise quality, speed, and productivity. You don't need to be an ML researcher, but you should be using AI tools well across the SDLC: in test design and triage, in exploratory prompts, and in helping the squad adopt them safely. You should also be sharpening your thinking on how to test GenAI features themselves.
- Help shape engineering and quality strategy with Tech Leads, Engineering Managers, and the Head of Quality Engineering. Automation foundations, performance and non-functional approach, escaped-issue triage, how we measure quality, where we invest, and how the QE enablement function operates as we scale it.
Requirements
What you’ll need- You've owned the quality of production systems at meaningful scale, and lived with what your tests caught and what they missed.
- You have a strong understanding of test design and a clear view on when to apply different techniques.
- You're proficient in at least one mainstream language (TypeScript, Python, Java, C#) and comfortable writing well-structured test code that other engineers can read and change.
- You've designed and operated automation in modern frameworks (Playwright, Cypress, or equivalents) and have a clear view on where they earn their keep and where they don't.
- You've worked with CI/CD pipelines (GitHub Actions, Jenkins, or similar) and know how to place tests for fast, reliable, meaningful feedback.
- You're comfortable in distributed, multi-tenant SaaS: microservices, cloud (AWS preferred; transferable experience welcome), and containerisation.
- You have working awareness of non-functional concerns (performance, security, accessibility) even if your depth is in one of them.
- You enjoy working with Product and Design as partners who shape what gets built, rather than as a service desk that hands you tickets.
- You're curious about AI tooling and product applications, and you want to help build a learning culture rather than wait for a training catalogue.
Benefits
Comp & perks- Senior quality engineering work at a company where AI is real, in production, and a core part of how customers get value. Not a side-of-desk experiment.
- A focused engineering organisation where your work is visible, your decisions matter, and the path from idea to customer is short.
- Investment in your growth: coaching, learning time, exposure to challenging problems, and a clear IC track if you want to keep deepening technically.
- Contributory pension plan.
- 33 days annual holidays, flexible working, and length of service entitlement.
- Health Insurance.
- Loyalty Share Scheme.
- Enhanced Maternity and Paternity.
- Employee Assistance Programme.
- Electric Vehicle Salary Sacrifice.
- Cycle to Work Scheme.
- Calm and Mindfulness sessions.
- A day of leave to volunteer for charity or dependent day.
- Regular Company Social Events.
- Yearly Development Retreat.
ATS Keywords
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Hard Skills & Tools
test designautomation strategyAPI testingUI testingexploratory testingCI/CDnon-functional testingprogramming (TypeScript, Python, Java, C#)automation frameworks (Playwright, Cypress)AI tooling
Soft Skills
coachingmentoringcollaborationcommunicationproblem-solvingcuriosityleadershipfacilitationcritical thinkingadaptability