Senior Quality Engineer

Senior quality engineering at Opus 2 is hands-on, high-trust, and works across teams. You'll lead complex, often ambiguous quality work from problem to production, coach squads to own their own quality, raise the bar on the engineers around you, and help shape how we build software in a moment where AI is changing the work week to week. You'll build quality into how multiple squads, and the wider organisation, design, ship, and operate software, as part of the Quality Engineering enablement function.

You can grow toward Principal QE or staff-level technical leadership from here. This is an IC role, and the day-to-day is engineering with influence, not management.

What you'll do

• 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.

The shape we're hiring for

We're hiring T-shaped QEs: broad across the quality disciplines and the team's stack, deep in at least one area. UI automation, API and contract testing, performance, security testing, accessibility, test data engineering, or another domain where you can show real expertise. We care more about how you think than how many tools you've used.

• Depth in something. You can name a quality domain where you're the person colleagues come to.
• Breadth that lets you cover the whole SDLC. Acceptance criteria, unit, integration, API, UI, exploratory, performance, production signal. You reason across the stack, not one slice of it.
• Builder, not gatekeeper. You raise the squad's collective ability to ship with confidence.
• Ownership that runs from idea to production and into how it operates. You're accountable for outcomes: building and maintaining customer confidence in our products, not for tests written.
• Steadiness under pressure. When delivery is uncertain or risk is high, you're a stabilising presence. Calm, structured, and clear about what's known and what isn't.
• Coaching disposition. You explain things clearly, give review feedback that grows people, and lift the team's median rather than its peak. You also receive feedback without defensiveness.
• Change disposition. You treat the AI-driven shift in software as the job rather than disruption to it. You learn fast, change your mind when the evidence does, and help colleagues do the same.

You'll be a strong fit if

• 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.

You might be a less good fit if

• You see quality as a gatekeeping function and yourself as the gate.
• You want to specialise narrowly in one testing discipline and not branch outside it.
• You'd rather not spend time growing developers and QEs around you. At this level, that's a core part of seniority.
• You're sceptical of AI tooling on principle and would rather wait to see whether it settles before engaging. At this level we expect you to be helping the squad work out what good looks like.
• You'd prefer a settled, high-process environment over one that's actively building its scaffolding.

You find rapid change in tools and ways of working draining rather than energising.