Initialize IT

Quality Engineering (QE) Architect/Lead - York (2/3 days) - 12 months - £545 Role QE Architect is the strategic and hands-on Quality Engineering leader responsible for defining, architecting, and governing the enterprise-wide quality engineering capability across the Tech Transformation portfolio. The role enables a product-led delivery model by embedding continuous testing, automation-first, shift-left quality practices, risk-based assurance, and flow engineering principles throughout the software development life cycle. Experience & Qualifications 12+ years of experience in Quality Engineering, Software Engineering or Test Automation. Minimum 5 years' operating as QE Architect/Principal Quality Engineer or Enterprise QE Lead level. Proven experience designing and scaling enterprise automation frameworks. Demonstrable expertise implementing Quality Engineering capabilities across large transformation portfolios. Strong experience with cloud, APIs, enterprise integration and data platform testing. Experience supporting Agile, Product-led and DevOps delivery models. Experience implementing TDD, BDD and Continuous Testing practices. Experience within Financial Services, Insurance or highly regulated industries preferred. Key Responsibilities 1. QE Strategy, Architecture & Transformation Define and maintain the Tech Transformation Quality Engineering Architecture and target-state quality operating model. Establish enterprise standards for automation, continuous testing, quality gates, test observability, and release assurance. Drive adoption of engineering-led quality practices aligned to DevOps and Flow Engineering principles. Design scalable QE frameworks that support Digital, Workbench, Data, AI and Integration platforms. Define and govern end-to-end integration testing to ensure seamless data flow, business process integrity, and operational reliability across core Policy, Claims, D365, Power Platform, API, and downstream enterprise systems Create reusable quality engineering assets, accelerators and reference architectures to increase delivery efficiency across programmes. Partner with Architecture, Engineering and Product leadership to embed quality from ideation through production. 2. Automation Architecture & Continuous Testing Architect and evolve enterprise automation frameworks covering UI, API, Data, Integration, AI and Non-Functional testing. Drive automation-first delivery ensuring automated validation is Embedded throughout CI/CD pipelines. Define testing strategies across the testing pyramid, ensuring automation is implemented at the most effective layer. Establish standards for: UI automation API automation Contract testing Data quality testing Integration testing Accessibility testing Performance testing Security testing AI model validation Promote Test Driven Development (TDD), Behaviour Driven Development (BDD), Specification by Example and Shift-Left testing practices. Design quality engineering solutions supporting feature teams, platform teams and product squads. 3. AI-Led Quality Engineering Lead adoption of AI-assisted and Agentic Testing capabilities. Define enterprise standards for AI-generated test design, test automation generation, self-healing automation and intelligent defect analysis. Drive effective use of GitHub Copilot, Claude and future AI engineering assistants. Establish approaches for ML model validation, prompt testing, AI workflow assurance and responsible AI testing. Identify opportunities to improve QE productivity through AI-driven risk analysis and predictive quality insights. 4. Technology & Platform Quality Architecture Own quality engineering strategy and architecture across: Digital CX Platforms OutSystems Business Applications Microsoft Dynamics 365 Microsoft Power Platform Data & Analytics Platforms GCP-based solutions SQL platforms AI product ecosystems Power BI Integration Platforms Azure APIM Event-driven integrations AI & Intelligent Products Underwriting Intelligence solutions ML-powered products Email Intake and Fraud/Coverage Assessment platforms 5. Engineering Excellence & Governance Define enterprise quality KPIs and engineering metrics. Establish quality governance processes supporting risk-based decision making. Define release readiness standards and quality gates. Provide independent assurance for high-risk and business-critical initiatives. Lead defect prevention strategies using root cause analysis and quality trend insights. Standardise reporting using Power BI, Allure, Azure DevOps dashboards. Ensure regulatory, audit and operational risk requirements are appropriately addressed. 6. Capability Building & Technical Leadership Act as the senior technical authority for Quality Engineering across the Tech Transformation portfolio. Coach and mentor QE Leads, SDETs, Automation Engineers and programme test teams. Develop engineering communities, standards and knowledge-sharing practices. Drive adoption of modern testing approaches across Product, Engineering and Delivery teams. Build internal capability and reduce dependency on external suppliers through coaching and framework reuse. Promote consistent engineering practices across all delivery teams. Required Technical Expertise Programming Languages Deep hands-on expertise in: TypeScript, JavaScript, C# Python, PyTest, SQL Strong understanding of: Object-oriented programming API development and testing Data engineering concepts Cloud-native architectures Microservices architectures Automation & Testing Tools UI Automation Playwright, BrowserStack, Applitools Cucumber/Reqnroll API Automation RestAssured, Postman, Newman, RESTSharp Email Services mailinator Data Testing PyTest, SQL Validation, Databricks Notebooks, Prefect Performance & NFR JMeter, k6, Accessibility Testing (JAWS), Security Testing (OWASP ZAP) Delivery & DevOps Azure DevOps Azure Repos, Pipelines Jira, Xray Reporting & Observability Power BI, Allure AI Engineering GitHub Copilot Claude Agentic AI Testing Solutions