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About the Role

The Quality Engineering (QE) Technical & Transformational Leader is responsible for driving QE modernization, technical excellence, and large-scale transformation across Client’s multiplatform, multiportfolio environment. This role combines deep technical authority, strategic consulting, transformation ownership, and organizational leadership, ensuring QE becomes a value-generating, data-driven engineering discipline.

Responsibilities

• Architect and drive end-to-end QE & Testing transformation aligned to Client’s engineering, digital, and modernization roadmap.
• Define and own QE operational model evolution, embedding continuous testing, shift-left, shift-right, DevOps alignment, automation-first culture, and AI/GenAI adoption.
• Identify and drive transformation levers such as automation scaling, test data modernization, environment optimization, and productivity uplift.
• Partner with domain leaders to introduce modern testing practices (insprint automation, service virtualization, early performance testing, observability, etc.).
• Bring exceptionally deep technical expertise across automation frameworks (UI, API, Mobile, Performance, CI/CD), QE tooling and engineering ecosystems, Test Data Management, Cloud testing, Environment strategy, and GenAI-powered test design, data creation, failure analysis.
• Build and govern standard frameworks, reusable assets, accelerators, and next-gen engineering solutions.
• Evaluate, propose, and institutionalize new tooling, frameworks, and engineering approaches through innovation, benchmarking, and continuous improvement.
• Present complex technical concepts clearly to Client’s senior leadership, including CIO, CTO, QE Heads and Portfolio Directors.
• Navigate challenging conversations with clarity, data, confidence, and strategic storytelling, especially in performance, productivity, and transformation reviews.
• Establish KPIs, productivity metrics, and value dashboards for QE across programs.
• Lead analytics-driven decision-making on Productivity improvement, Defect trends, Cost of quality, Test efficiency & cycle time, and Automation ROI.
• Managed team-size of 300+ in large programs in multi-years engagement.
• Lead distributed teams across functional, automation, performance, environmental, TDM, release engineering, and AIQE capabilities.
• Mentor QE leaders, architects, and managers to uplift skills, competency, and engineering maturity.
• Align teams to outcomedriven delivery, not just “lightson” operations.
• Evaluate and integrate Client’s tool chain, aligning QE innovation with Client’s AI architecture direction.

Requirements

• 20–25+ years in QE engineering, transformation, and automation leadership.
• Mastery of Playwright, Appium, Selenium, Cypress, Java.
• Mastery of API Automation (REST Assured, Karate, Postman).
• Mastery of Performance testing tools (JMeter, LoadRunner).
• Mastery of Cloudnative testing (Azure, AWS, GCP).
• Mastery of test orchestration and CI/CD pipelines.
• Mastery of TDM, environment strategy, and observability tools.
• Outstanding communication, influence, and executive presence.
• Proven ability to operate in demanding, politically dynamic client environments.
• Strong analytical and problem-solving skills.

Skills

• QE modernization
• Technical excellence
• Large-scale transformation
• Automation frameworks
• DevOps alignment
• AI/GenAI adoption
• Automation scaling
• Test data modernization
• Environment optimization
• Productivity uplift
• Modern testing practices
• Insprint automation
• Service virtualization
• Early performance testing
• Observability
• Automation frameworks (UI, API, Mobile, Performance, CI/CD)
• QE tooling
• Engineering ecosystems
• Test Data Management
• Cloud testing
• Environment strategy
• GenAI-powered test design
• GenAI-powered data creation
• GenAI-powered failure analysis
• Standard frameworks
• Reusable assets
• Accelerators
• Next-gen engineering solutions
• Innovation
• Benchmarking
• Continuous improvement
• Executive communication
• Stakeholder management
• Data-driven delivery
• Productivity tracking
• Value tracking
• KPI establishment
• Productivity metrics
• Value dashboards
• Analytics-driven decision-making
• Automation ROI
• Leadership of large, multi-disciplinary QE teams
• AI/GenAI integration
• Playwright
• Appium
• Selenium
• Cypress
• Java
• API Automation
• REST Assured
• Karate
• Postman
• Performance testing
• JMeter
• LoadRunner
• Cloudnative testing
• Azure
• AWS
• GCP
• Test orchestration
• CI/CD pipelines
• TDM
• Observability tools

Location

• Norwich

Work Type

• Full-time

Experience Level

• Senior
• 20-25+ years

About the Company

• Client is a large organization with a multiplatform, multiportfolio environment.