Quality Engineering Lead

Job Description

We're looking for a Quality Engineering Lead to join our growing team.

This is a senior technical leadership role focused on shaping, advising and implementing modern quality engineering practices across software delivery environments.

You may come from a software engineering, SDET, test architecture, platform engineering or solution architecture background, with significant experience embedding quality into engineering practices, helping teams prevent defects, manage risk and deliver software with confidence.

You will work with engineering, architecture, product and delivery teams to define and implement test strategies and quality approaches that support continuous delivery, fast feedback, reliable automation, responsible use of AI, non-functional quality and sustainable engineering practices.

This is not a traditional QA management role focused on coordinating test execution. It is a senior technical leadership role focused on improving how teams build, test, release and learn from software. The role is client‑facing and may operate across one or more delivery teams or accounts, combining advisory leadership with targeted hands‑on implementation.

You will also work with senior leaders across Endava's Quality Engineering discipline to help evolve standards, practices, accelerators and capability, ensuring quality engineering continues to support successful delivery outcomes for clients.

• Define, own and lead quality engineering and test strategies for client and internal delivery teams.
• Provide authoritative guidance on test planning, quality engineering, automation, AI‑assisted engineering and continuous delivery practices.
• Design pragmatic test architectures that provide fast, reliable feedback across functional, integration, contract, API, UI, non‑functional, security and operational quality concerns.
• Enable the successful implementation of test strategies through clear milestones, lightweight evidence‑based release readiness criteria, feedback mechanisms, risk management and measurable outcomes.
• Help teams shift quality earlier through better engineering practices, testability, automation, AI‑enabled productivity and defect prevention.
• Assess delivery pipelines and work hands‑on with engineers to improve automation frameworks, test tooling, pipeline feedback, non‑functional testing practices and quality metrics.
• Evaluate where AI‑assisted engineering tools can safely improve test design, code review, automation generation, defect analysis, exploratory testing, risk assessment and documentation, while managing associated risks.
• Identify quality risks, delivery constraints and systemic issues, then translate them into clear delivery, commercial and business impact and drive practical corrective and preventative action.
• Coach engineers, testers and delivery leaders on quality engineering principles, effective test strategy and responsible use of AI.
• Contribute to Endava's quality engineering capability, standards, accelerators, communities of practice and thought leadership.

• Strong technical background in software engineering, SDET, test architecture, solution architecture, platform engineering or a related discipline.
• Significant experience in quality engineering, test strategy, automation and modern software delivery.
• Hands‑on experience with at least one modern programming language and the ability to review, understand and influence code.
• Strong understanding of CI/CD, automated pipelines, version control, deployment practices and release confidence.
• Experience defining and implementing test strategies for distributed systems, APIs, cloud platforms, microservices, data platforms or complex enterprise applications.
• Practical knowledge of automation patterns, test pyramid principles, contract testing, stubs/mocks, service virtualisation and environment management.
• Experience with non‑functional testing, including load, performance, reliability, resilience, scalability, security and operational readiness.
• Experience using, evaluating or guiding AI‑assisted engineering tools for software quality, automation, risk analysis or developer productivity, with…