Software Quality Assurance & Process Engineer

About the Role

We are seeking an experienced Software Quality Assurance & Process Engineer to join our team. This role is critical in maintaining and advancing our software quality standards across multiple programmes. The successful candidate will own quality assurance planning, drive ISO 27001 compliance integration, manage software audits, conduct rigorous software testing — including validation of AI-assisted development outputs — and provide hands-on quality oversight for ongoing development projects.

1. Software Quality Assurance Planning

• Develop, execute, and maintain the Standard Software Quality Assurance Plan (SWQAP) in alignment with organisational standards and timelines.
• Ensure QA plans cover all stages of the software development lifecycle (SDLC).
• Track QA milestones and produce regular progress reports for stakeholders.

1. ISO 27001 Compliance

• Integrate ISO 27001 clauses and compliance requirements within the Software Project Management (SW PM) framework.
• Conduct gap analyses and coordinate with relevant teams to close compliance gaps.
• Maintain up-to-date documentation aligned with ISO 27001 requirements.

1. Software Audit Management

• Lead the closure of annual software audits, ensuring all findings are tracked and resolved.
• Establish and maintain robust audit processes and ensure process documentation is properly set up and followed.
• Liaise with internal and external auditors to facilitate smooth audit cycles.

1. Project Programme Quality Support

• Complete Software Quality Assurance Plan (SWQAP) for internal programmes.
• Prepare and present software-related quality updates to BA(Quality) stakeholders across the broader organisation.
• Collaborate with MRL on System Safety activities and other project quality deliverables as required.

1. Software Development Control & Monitoring

• Provide ongoing quality oversight and control monitoring for software development activities across assigned projects
• Ensure software development processes comply with defined quality standards and project requirements.
• Identify risks and non-conformances early and work with development teams to implement corrective actions.

1. Software Testing & AI-Assisted Development Validation

• Assist plan, design, and execute comprehensive software test strategies covering functional, regression, integration, and system-level testing across programme.
• Assist software version release management, ensuring all releases meet defined quality gates before deployment.
• Review and validate test plans, test cases, test results, and release documentation to ensure completeness and traceability.
• Define and enforce test coverage standards for AI-generated code, ensuring outputs are subjected to the same rigorous quality bar as manually written code.
• Stay current with emerging best practices for testing AI-integrated systems, including prompt validation, model output consistency checks, and AI tool risk assessment.
• Document and communicate test metrics, defect trends, and quality risks to programme stakeholders in a clear and actionable manner.

Requirements

• Degree in Computer Science, Software Engineering, Information Technology, or a related discipline.
• Minimum 5 years of experience in software quality assurance or a related engineering role, with direct hands-on testing experience.
• Prior experience in defence, government, or safety-critical systems environment is highly advantageous.

• Strong knowledge of software QA methodologies, audit processes, and SDLC frameworks.
• Familiarity with ISO 27001 standards and experience integrating compliance requirements into engineering processes.
• Experience developing and executing Software Quality Assurance Plans (SWQAP).
• Proficiency in software version control and release management practices.
• Hands-on experience in designing and executing test plans, test cases, and defect management across multiple test types (functional, regression, integration, UAT).
• Familiarity with AI-assisted development tools (e.g. GitHub Copilot, Cursor, ChatGPT Code Interpreter, or similar) and an understanding of the quality risks they introduce.
• Experience with test automation frameworks and CI/CD integration (e.g. Selenium, pytest, Jenkins, GitLab CI) is an advantage.
• Knowledge of system safety concepts and quality management systems is a plus.

• Strong analytical and problem-solving skills with a keen eye for detail — especially when reviewing AI-generated artefacts.
• Excellent communication skills — able to prepare and present quality and test reports to cross-functional stakeholders.
• Self-directed, organised, and capable of managing multiple concurrent workstreams.
• Collaborative team player with the ability to work across different business areas and external partners.
• Curious and adaptable mindset — willing to continuously learn as AI tooling and development practices evolve.