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Mid-Level QA Engineer

Job in Basingstoke, Hampshire County, RG21, England, UK
Listing for: Stratospherec Ltd
Full Time position
Listed on 2026-08-05
Job specializations:
  • Software Development
    AI QA / Validation Engineer
Salary/Wage Range or Industry Benchmark: 50000 - 60000 GBP Yearly GBP 50000.00 60000.00 YEAR
Job Description & How to Apply Below

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.
JOB RESPONSIBILITIES:
  • 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.
AI‑AUGMENTED QA & INNOVATION:
  • 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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