Senior Quality Engineer, Opus 2
Salary not provided
MongoDB
AWS
Docker
Kubernetes
TypeScript
Python
C#
Java
Elasticsearch
Go
Postgres
Jenkins
Cypress
Postman
Playwright
Senior and Expert level
Edinburgh
Legal software & services
Be an early applicant
Legal software & services
201-500 employees
B2BData storageLegalCommunication
Be an early applicant
Salary not provided
MongoDB
AWS
Docker
Kubernetes
TypeScript
Python
C#
Java
Elasticsearch
Go
Postgres
Jenkins
Cypress
Postman
Playwright
Senior and Expert level
Edinburgh
201-500 employees
B2BData storageLegalCommunication
Company mission
To design, develop, and deliver industry-leading solutions that transform the dispute lifecycle —empowering legal professionals to maximise the value they deliver to clients.
Role
Who you are
- 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'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
- 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
What the job involves
- 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
- 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
- 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
Our take
Documentation, clients and teams are all multifarious in legal proceedings, and therefore provide unique logistical problems. Opus 2 aims to meet the needs of the modern courtroom by providing digital solutions in an age of remote hearings.
The company provides e-bundles that seek to solve these problems. Whilst courtrooms may use existing video software to conduct hearings, Opus 2 integrates this software with other elements (such as data storage and documentation) in order to streamline the process and ultimately save time for everyone. The company offers virtual workspaces on a secure cloud platform, streamlining legal work for both lawyers and clients.
Opus 2 continually invests in developing its software in the UK and internationally and facilitates this by hiring new talent. A recent partnership with SeeUnity is set to help achieve this.
Kirsty
Company Specialist at Welcome to the Jungle
Insights
13% employee growth in 12 months
Company
Company HQ
Holborn, London, UK
Leadership
Graham Smith-Bernal
(CEO)Founded LiveNote, the world's most widely used litigation support tool, before starting Opus 2 in 2008.
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