Quality Engineering Lead at Endava

London, England, United Kingdom -

Full Time

Start Date

Immediate

Expiry Date

23 Sep, 26

Salary

0.0

Posted On

25 Jun, 26

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Quality Engineering, Test Strategy, Automation Frameworks, CI/CD, AI-Assisted Engineering, Non-Functional Testing, Stakeholder Management, Software Architecture, API Testing, Contract Testing, Risk Management, Cloud Platforms, Microservices, SDET, Consulting, Performance Testing

Industry

IT Services and IT Consulting

Description

Company Description Technology is our how. And people are our why. For over two decades, we have been harnessing technology to drive meaningful change. By combining world-class engineering, industry expertise and a people-centric mindset, we consult and partner with leading brands from various industries to create dynamic platforms and intelligent digital experiences that drive innovation and transform businesses. From prototype to real-world impact - be part of a global shift by doing work that matters. Endava is on an AI Native journey. As one of OpenAIs global partners we are committed to exploring (and helping our clients explore) the benefits AI can bring to productivity, effectiveness and accuracy. Our goal is to seize the AI-catalyzed growth moment to navigate this changing landscape and ensure ourselves and our clients thrive. 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. What you'll be doing 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. Qualifications Essential 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 awareness of risks such as false confidence, privacy, maintainability and unreviewed generated outputs. Ability to operate at both strategic and implementation levels: assess, advise, design, coach and build. Strong stakeholder management and consulting skills, with confidence influencing senior technical, delivery and client audiences. A pragmatic mindset focused on flow, risk reduction, engineering excellence, responsible innovation and measurable improvement. Desirable Experience working in consultancy, client-facing delivery or multi-team engineering environments. Experience operating at senior client level and advising on quality, delivery risk and engineering improvement. Familiarity with continuous delivery principles. Experience applying AI or machine learning concepts within software engineering, testing, quality analysis or delivery optimisation. Experience leading communities of practice, mentoring engineers or shaping organisational quality standards. Experience contributing to proposals, delivery assessments, capability development or quality improvement initiatives. Additional Information Discover some of the global benefits that empower our people to become the best version of themselves: Finance: Competitive salary package, share plan, company performance bonuses, value-based recognition awards, referral bonus; Career Development: Career coaching, global career opportunities, non-linear career paths, internal development programmes for management and technical leadership; Learning Opportunities: Complex projects, rotations, internal tech communities, training, certifications, coaching, online learning platforms subscriptions, pass-it-on sessions, workshops, conferences; Work-Life Balance: Hybrid work and flexible working hours, employee assistance programme; Health: Global internal wellbeing programme, access to wellbeing apps; Community: Global internal tech communities, hobby clubs and interest groups, inclusion and diversity programmes, events and celebrations. At Endava, we’re committed to creating an open, inclusive, and respectful environment where everyone feels safe, valued, and empowered to be their best. We welcome applications from people of all backgrounds, experiences, and perspectives—because we know that inclusive teams help us deliver smarter, more innovative solutions for our customers. Hiring decisions are based on merit, skills, qualifications, and potential. If you need adjustments or support during the recruitment process, please let us know.

Responsibilities

Lead the definition and implementation of modern quality engineering strategies and test architectures for client delivery teams. Focus on shifting quality earlier in the lifecycle through AI-enabled productivity, automation, and sustainable engineering practices.