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Digital / data / automationDigital / data / automation
Quality Assurance Tester
Quality assurance testers find bugs and problems in computer software before it reaches people using it. They test apps and websites thoroughly to make sure they work properly and are easy to use.
No degree needed for many routes
AI impact: high££ payDirect entry route
78
AI impact
how much AI is reshaping it
Robin · your guide
Curious about being a quality assurance tester? Here's the honest picture - what you'd really do, what you'd earn, and every way in. No need to decide anything yet.
What you'd actually do
As a quality assurance tester, you are responsible for catching problems before customers find them. You test new software and apps by using them the way a real person would - clicking buttons, entering data, checking that things work on different devices. When you find a bug, you document it carefully so that the programming team can fix it.
Your day involves planning what to test, creating test cases, and running through them methodically. You might test the same feature dozens of times in slightly different ways to find edge cases the developers missed. You use testing software tools that can run some checks automatically, so you can focus on the trickier manual testing. You need to think like both a user and a problem-solver - wondering how a real person might break the app or get confused. You work with developers and product managers, so you need to explain clearly what went wrong and where. As you progress, you might lead a testing team or specialise in performance testing - checking if an app can handle thousands of users at once.
1Design and execute comprehensive test plans and test cases.
2Identify, document, and track software defects using bug tracking systems.
3Collaborate with developers and product managers to understand features and requirements.
4Perform regression testing to ensure existing functionality remains intact.
5Utilize automated testing tools to streamline testing processes.
6Conduct performance testing to evaluate software responsiveness and stability.
7Review and analyze system specifications to ensure thorough testing coverage.
8Participate in Agile ceremonies, providing input on quality-related topics.
Career progression & pay
01
Getting in
Junior Quality Assurance Tester
£22,000 - £27,000
A degree in Computer Science or a related field; knowledge of testing methodologies.
As a Junior QA Tester, you will assist in executing test cases and documenting results. This role is ideal for recent graduates looking to gain hands-on experience in software testing.
02
Building up
Mid-Level Quality Assurance Tester
£30,000 - £38,000
2-4 years of experience in software testing; proficiency in automated testing tools.
In this role, you will lead testing efforts, mentor junior testers, and work closely with development teams to ensure quality standards are met. Your expertise will be crucial in improving testing processes.
03
At the top
Senior Quality Assurance Tester
£42,000+
5+ years of experience; strong leadership skills; expertise in test automation and performance testing.
As a Senior QA Tester, you will oversee the testing strategy for projects, manage a team of testers, and liaise with stakeholders to ensure quality objectives align with business goals.
Degrees that lead here via Digital & Technology
Degree options are mapped from subjects - explore the buckets to find related courses.
Apprenticeships that lead here
Who hires - top UK employers
ThoughtWorks
A global software consultancy that focuses on software development and quality assurance.
FDM Group
A professional services provider that recruits, trains, and deploys IT and business consultants.
Capgemini
A global leader in consulting, technology services, and digital transformation.
Accenture
A leading global professional services company with extensive experience in quality assurance.
Cognizant
A multinational technology company that provides IT services, including quality assurance.
AI & the future of this job
QA testing sits at the sharp end of AI disruption because writing test scripts, generating test cases from requirements, and running regression suites are precisely what modern AI coding agents do well. Tools like GitHub Copilot, Testim, and autonomous testing platforms already handle significant portions of what junior and mid-level testers spend their days doing. The entry-level pipeline is contracting fast, with many companies replacing manual QA headcount with AI-assisted automation that requires far fewer human operators to supervise. The roles that survive will demand deep systems thinking, security awareness, and the ability to interrogate AI-generated test outputs critically rather than just produce them.
Within 5 Years
Significant role contraction
By 2031, autonomous testing platforms will handle the bulk of regression, functional, and load testing with minimal human setup. Junior manual testing roles will be largely absorbed or eliminated across mid-to-large tech companies. Remaining QA professionals will be expected to architect testing strategies, evaluate AI-generated test coverage for gaps, and lead quality thinking at a product level. Salaries for those who adapt upward will hold, but the volume of available positions will shrink noticeably.
Within 10 Years
Specialist survival only
Within a decade, standalone QA tester as a job title will be rare outside highly regulated industries such as medical devices, aerospace, and financial infrastructure. In those sectors, human sign-off and interpretive judgement will remain legally or ethically required. Elsewhere, quality assurance will be a competency owned by engineers and product teams, supported by AI tooling rather than a separate department. Those who have repositioned into security testing, AI validation, or test engineering leadership will remain employable and well-compensated.
Within 20 Years
Role largely dissolved
Over a twenty-year horizon, the QA tester as a distinct occupational category is unlikely to survive in mainstream software development. AI systems will design, execute, and interpret test outcomes as a native part of the development pipeline, requiring only high-level human governance. The professionals who thrived will have long since migrated into adjacent roles: AI systems auditing, software reliability engineering, or product quality leadership. Those who did not adapt early will find re-entry into tech careers significantly harder.
How to stay ahead
Shift from doing tests to designing test strategy
Move away from hands-on test execution and towards owning the quality architecture of a product. Learn to define coverage criteria, risk-based testing frameworks, and quality metrics that no AI tool will spontaneously generate without human direction. This repositions you as the person overseeing the machine, not competing with it.
Specialise in regulated or safety-critical sectors
Industries like medical software, avionics, automotive systems, and fintech operate under legal frameworks that require traceable, human-verified testing processes. Certifications such as ISTQB Advanced or sector-specific qualifications in IEC 62304 or ISO 26262 make you relevant in spaces where AI alone cannot sign off on compliance. These niches will remain protected for many years.
Build security and penetration testing skills
AI testing tools are effective at functional validation but remain weak at adversarial thinking, creative exploit discovery, and social engineering surface assessment. Adding ethical hacking skills and pursuing certifications like CEH or CompTIA PenTest+ transforms your profile from a shrinking role into a growing one. Cybersecurity demand is structural, not cyclical.
Learn to audit and validate AI systems themselves
As companies deploy AI in their own products, the need to test AI behaviour, bias, fairness, and edge-case failure is an emerging specialism with very few qualified practitioners. Understanding model evaluation, prompt robustness testing, and responsible AI frameworks positions you at the frontier of what quality assurance will mean in five years. Courses from institutions via the Alan Turing Institute or Google's Responsible AI curriculum are practical starting points.
How to get in - your routes
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