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Head of QA

Job in Greater London, London, Greater London, W1B, England, UK
Listing for: La Fosse
Full Time position
Listed on 2026-10-26
Job specializations:
  • Software Development
    AI QA / Validation Engineer
Salary/Wage Range or Industry Benchmark: 90000 - 120000 GBP Yearly GBP 90000.00 120000.00 YEAR
Job Description & How to Apply Below
Quality Engineering Lead
  • London based tech insurer – highly flexible hybrid working
  • Salary: £90,000 – £120,000
  • Bonus up to 15%
  • Please note:

    This role does not offer sponsorship, candidates will be required to have a valid right to work in the UK.

We're working with a rapidly scaling, technology-led insurance business looking for a Quality Engineering Lead to take ownership of quality engineering across its software delivery function.

This is a hands‑on leadership role, combining ownership of QA strategy, standards and automation with responsibility for driving quality across multiple engineering teams. The role operates primarily through matrix management.

The Role:

A key focus will be strengthening quality throughout the software development life cycle, reducing defects reaching production and moving away from a reliance on manual regression testing towards a more automated and scalable approach.

You'll be responsible for:

  • Defining and driving the QA and test automation strategy
  • Establishing quality standards across engineering teams
  • Leading QA through a matrix management model, influencing teams
  • Improving and expanding existing test automation
  • Reducing reliance on manual regression testing
  • Ensuring software releases demonstrably meet agreed quality standards
  • Reviewing how developers, QAs and API teams approach testing
  • Embedding quality throughout the Agile software development lifecycle
  • Supporting and developing QAs embedded within engineering squads
  • Helping to hire and build out the QA team as the business grows
  • Leading by example and demonstrating what good quality engineering looks like
  • Exploring how AI can be practically introduced into testing and automation – Exploring how AI can be practically introduced into testing and automation, with an early focus on identifying a quick win within the first 90 days to improve automation and reduce manual testing effort
  • Pre existing experience within financial services will not be essential however experience working with large data sets and data heavy environments is key.
Technology Environment

You'll be working across an environment that includes:

  • Playwright for web application testing
  • API testing with Postman
  • C# within the testing environment
  • Significant data-focused testing
  • Agile software delivery
  • Test automation and regression testing
You'll ideally have:
  • Strong experience in QA / Quality Engineering and test automation
  • Experience owning or leading a quality engineering strategy
  • Strong hands‑on knowledge of test automation frameworks and approaches

    Experience with Playwright or comparable modern automation tooling
  • Strong API testing experience
  • Experience working with data‑heavy applications or platforms
  • A track record of reducing manual regression testing through automation
  • Experience leading and influencing teams through a matrix structure
  • The ability to set standards and drive change across development and QA teams
  • Experience mentoring, interviewing or helping grow QA teams
  • A strong understanding of how quality should be embedded throughout the SDLC
  • An interest in using AI within software testing and quality engineering
Working Environment

The business offers a highly flexible approach to office working. There is a London office available, but there isn't a requirement to attend a set number of days each week.

You'll primarily work flexibly, coming into the office as and when required for specific meetings or collaboration.

There is also flexibility to work abroad once established in the role, subject to company and location restrictions.

Interview Process: 2 stage interviews
  • Stage 1 – Virtual interview (30–45 minutes)

An initial conversation focused on your experience, cultural fit and discussing your background in more detail.

Case Study:
Successful candidates will be given a case study ahead of the final interview. You'll be encouraged to use AI as part of the exercise, with the focus on explaining how you used it, where it added value and where your own judgement was required.

  • Stage 2 – In-person technical interview (approximately 1 hour)

A more technical session with members of the engineering team, discussing your approach, technical experience and case study.

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