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.

How we work

Opus 2 builds the platform that leading legal teams use to run their most complex work: a distributed, multi-tenant SaaS platform with API-first surfaces, where security, privacy, and compliance are first-class concerns. The stakes for our customers are real, so we care about quality. We also move fast and ship, because the alternative is irrelevance.

Strong ownership. Squads own their products end-to-end, from the customer outcome through to operating them in production. Teams own the quality of what they ship, and Quality Engineering is an enablement function alongside them: coaching, surfacing tooling gaps, and spreading what works across the organisation.
Quality built in, not bolted on. Prevention over detection, automation first, data-driven decisions, customer-centric focus. Testing happens across the whole lifecycle, not as a stage at the end.
Pragmatic engineering. We favour simple, testable solutions over premature abstraction. Risk-based over exhaustive. We use data where it informs a real decision.
A learning and improvement culture. We're building an engineering organisation that learns and adapts at the pace AI is forcing on the work. That's the bar for hiring, growth, and how we run the team.
Coaching as part of seniority. Senior engineers and QEs help juniors, mid-levels, and each other grow. We protect that time on calendars.

A work in progress

Opus 2 is in real transition. AI is reshaping how our customers work and how we build software, and we're investing in the engineering organisation, including how we do quality, to keep pace. Some of that is already settled; other parts are still being shaped. The Quality Engineering strategy sets the direction, and the practices that deliver on it are being put in place team by team.

Quality Engineering itself is changing shape. We're moving from a fully embedded model, where each squad had its own QE owning that squad's testing, to a quality enablement function: a cross-cutting team that coaches squads to own their own quality outcomes, identifies and closes tooling gaps, and spreads what works on one team to all of them. The bar is teams owning quality themselves, with QE making that possible at the scale of the whole organisation. Seniors do a lot of the shaping of this: what coaching looks like in practice, which tooling investments compound, and how knowledge moves between teams.

If you want a fully-paved path, this isn't it yet. If you want to be an agent of change in a team that's clear about where it's going and pragmatic about how to get there, there's real leverage here. We're hiring people who'll help us shape this, not just slot into it.

Tech you'll work with

We pick tools to fit the problem, and we have a clear sense of where we're heading.

Automation: Playwright for UI; Postman and code-first API tests; unit and integration tests in the same languages as the code under test.
Languages: TypeScript and Go where we're investing; Java where it's established.
CI: GitHub Actions as the primary pipeline.
Cloud & infra: AWS, Kubernetes, Docker.
Data: Postgres, MongoDB, OpenSearch / Elasticsearch.
AI: GenAI features already in production (LLMs, retrieval, agentic workflows), with more on the way. Testing these well is part of the job at this level.

You don't need to know all of these on day one. You should be ready to learn what you don't.

Working for Opus 2

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.

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