Mid-Level QA Engineer
Listed on 2026-08-05
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Software Development
AI QA / Validation Engineer
QA Software Tester - Mid Level
Salary - £50k to £60k
Weekly travel to UK office in Basingstoke, Hampshire
Our client provides an enterprise-grade software platform for managing, monitoring, controlling, and automating connected work spaces. You will be part of a small QA Test Team working on their SaaS platform that the is used by their Global Blue-chip clients.
You will be a part of a fast-paced team of self‑starters that are excited to challenge the emerging technology space around near real-time remote management platform capabilities for global devices (i.e. AV, BMS, IoT) s role is a fantastic opportunity to grow your knowledge and skill sets with a talented team of thought leaders, sales leaders, engineers, and marketers.
JOB DESCRIPTION:The Quality Assurance Engineer will help develop, plan, manage, and execute test plans for all software products. You will be responsible for helping to produce robust, high-quality software using your technical experience, attention to detail, and close collaboration with your engineering partners and QA peers.
This role requires a strong understanding of functional, integration, system, and automated testing within a distributed SaaS environment. The ideal candidate is curious, technically capable, detail-oriented, and interested in leveraging modern AI‑assisted tools and workflows to improve software quality, test coverage, and team efficiency.
TECHNICAL ENVIRONMENT & SCOPE:- Test distributed SaaS platform components across cloud-hosted and client-installed environments.
- Perform end-to-end testing across web applications, backend services, APIs, databases, and device integrations.
- Test client‑side or on‑premise applications, including installation, configuration, upgrade paths, service validation, permissions, environment dependencies, and connectivity to cloud-hosted services.
- Validate integrations across APIs, Webhooks, third‑party systems, and connected platform components.
- Validate alerting, telemetry, reporting, and event‑driven workflows across multiple system components.
- Support testing efforts involving scalability, reliability, system behavior, and performance validation.
- Collaborate closely with engineering teams operating within Agile development environments.
- Develop test cases and test plans based on requirements, specifications, engineering input, and collaboration with QA peers.
- Identify opportunities for automation and develop or maintain automated test coverage across UI, API, and integration testing layers using tools such as Smart Bear Test Complete.
- Execute and manage functional, integration, regression, and system testing efforts while communicating progress, risks, and blockers.
- Configure and maintain test environments, servers, integrations, and test data required for execution.
- Perform hands‑on integration testing in the Basingstoke office, including setting up testing environments, configuring devices, and validating software behavior with physical hardware.
- Help diagnose defects, identify probable root causes, and collaborate with engineering, Product and business teams to prioritize and validate resolutions.
- Validate end‑to‑end workflows and system behavior across multiple interconnected services and components.
- Assist with API, integration, backend data validation, and CI/CD testing initiatives where applicable.
- Identify, track, analyze, and report testing and quality KPI trends throughout the SDLC and release lifecycle.
- Help mature the QA SDLC by contributing ideas for improving processes, automation, efficiency, and communication.
- Leverage AI‑assisted development and testing tools (e.g., Git Hub Copilot or similar technologies) to improve QA workflows, efficiency, and test coverage.
- Experiment with AI‑driven approaches for generating functional, integration, and edge‑case test scenarios from requirements, specifications, APIs, and codebases.
- Use AI tools to accelerate test case creation, test data generation, defect investigation, and automation development.
- Help identify opportunities where AI can improve release quality, regression testing, and QA productivity.
- Contribute ideas and best practices…
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