Manager - Test Automation 2

Roles and Responsibilities

• Define and lead enterprise and programme-level Quality Assurance strategies aligned with business objectives, technology architecture, delivery models, and risk. Assess existing testing practices and establish QA transformation roadmaps, target operating models, governance frameworks, engineering standards, and measurable quality outcomes.
• Design scalable, maintainable, and fit-for-purpose test automation architectures covering UI, API, integration, component, contract, and end-to-end testing. Define automation frameworks, reusable components, test-data strategies, reporting, environment requirements, maintenance approaches, and technology selection based on application architecture, project requirements, scalability, maintainability, and overall QA strategy.
• Define and implement CI/CD-integrated Quality Assurance and continuous testing strategies that provide fast, reliable, and actionable feedback throughout the software delivery lifecycle. Establish appropriate test execution strategies across pull requests, builds, deployments, integration and staging environments, regression cycles, and production validation.
• Address and optimise the practical engineering challenges associated with continuous testing, including pipeline efficiency, test reliability, execution time, environment readiness, test-data management, dependencies, parallelisation, selective test execution, quality gates, and pipeline stability. Establish practices such as test impact analysis, risk-based test selection, mocking, tagging, and other optimisation techniques to improve feedback time and pipeline reliability.
• Define and monitor QA and CI/CD metrics including automation coverage, execution time, test reliability, flakiness, pipeline stability, defect leakage, release confidence, and other relevant engineering and business outcomes.
• Define and lead Performance Testing strategies for critical applications, services, and customer journeys, covering workload modelling, test planning, scripting, execution, scalability, capacity assessment, performance monitoring, bottleneck identification, detailed test-result analysis, performance optimisation, and performance regression.
• Lead detailed analysis of Performance Test results by correlating application, infrastructure, and monitoring metrics to identify performance bottlenecks, capacity constraints, resource utilisation issues, and system-level degradation. Translate findings into actionable recommendations for performance optimisation, scalability, capacity planning, and engineering improvements.
• Define and implement API, Contract, and Component Testing strategies, establishing the appropriate balance across component, contract, API, integration, UI, end-to-end, and performance testing based on application architecture, business risk, and delivery requirements.
• Define test planning and test case design approaches across programmes, ensuring appropriate test scope, scenarios, coverage, traceability, risk-based prioritisation, test data, environment requirements, entry/exit criteria, and execution strategies aligned with business and technical requirements.
• Partner with Development, DevOps, Architecture, Product, and Platform Engineering teams within and outside the organisation to embed quality throughout the software development and delivery lifecycle and promote shift-left, continuous testing, and engineering-led quality practices.
• Lead or significantly contribute to RFP, RFI, RFQ, presales, and client solutioning engagements from a Quality Assurance perspective. Translate client requirements and technology challenges into differentiated QA solutions, including QA strategies, automation architectures, CI/CD and continuous testing approaches, performance strategies, implementation roadmaps, effort estimates, resource models, timelines, assumptions, dependencies, risks, delivery approaches, and expected outcomes. Participate in client discovery sessions, solution workshops, proposal discussions, technical presentations, and solution defence activities.
• Drive the adoption of AI, GenAI, Agentic, and MCP-based testing across Quality Assurance, identifying and implementing high-value use cases such as test generation, automation code generation, test maintenance, test-data generation, failure and defect analysis, intelligent test selection, test optimisation, and test-result analysis. Lead the evaluation and adoption of AI-enabled solutions capable of planning, generating, executing, analysing, and adapting testing activities.
• Mentor and develop QA professionals across technical testing, test automation, performance testing, modern testing practices, solutioning, proposals, RFP/RFI/RFQ engagements, and client-facing activities. Provide technical guidance, knowledge sharing, coaching, and career development support while building strong testing capabilities and technical leadership within the team.
• Act as a trusted Quality Assurance advisor to senior stakeholders and clients, providing technical direction, influencing technology and delivery decisions, communicating risks and recommendations, and aligning QA outcomes with broader business objectives.

Professional and Technical Skills

• Extensive experience defining and executing Quality Assurance and Quality Engineering strategies, driving testing transformation initiatives, and establishing Testing Centres of Excellence (TCoE) across enterprise programmes.
• Proven expertise in Test Automation Strategy, Architecture, and Framework Design, with the ability to build scalable, maintainable, and reusable automation solutions across web, mobile, API, and cloud-based applications — selecting appropriate technologies based on application architecture, business risk, scalability, maintainability, and delivery requirements.
• Strong technical leadership in modern Quality Engineering practices, including automation-first approaches, shift-left and shift-right testing, test optimisation, and continuous quality improvement.
• Demonstrated success in managing and growing a Testing Practice, including capability development, competency building, resource planning, governance, offshore delivery management, and mentoring of QA and automation teams.
• Strong hands-on experience across API, Contract, Component, Integration, End-to-End, and Performance Testing, with a thorough understanding of modern testing strategies and the appropriate balance across test levels based on architecture, risk, and delivery requirements.
• Strong practical experience in Performance Testing, including workload modelling, test planning, scripting, execution, scalability and capacity assessment, performance regression, and optimisation. Demonstrated ability to analyse and correlate application, infrastructure, and monitoring metrics to identify bottlenecks, resource constraints, and scalability limitations — and provide actionable engineering recommendations.
• Strong practical experience integrating automated testing into CI/CD pipelines and DevOps delivery models, with the ability to design continuous testing strategies and address real-world challenges including test reliability, execution time, environment dependencies, test data, parallelisation, selective execution, pipeline stability, quality gates, and feedback optimisation.
• Experience with test execution optimisation practices such as risk-based test selection, test impact analysis, parallel execution, test tagging, mocking, test-data management, environment strategy, and automation maintenance.
• Strong understanding and practical experience of cloud technologies and cloud-native architectures, including validation of microservices, APIs, distributed systems, serverless architectures, and modern cloud platforms. Strong knowledge of containerisation technologies such as Docker and their application in test environment management and scalable automation execution.
• Proven experience in RFP, RFI, RFQ, presales, and client solutioning — including proposal development, QA solution design, effort estimation, resource planning, costing, technical presentations, client workshops, and solution defence. Ability to translate client requirements into competitive, practical QE solutions covering strategy, automation architecture, CI/CD, performance, delivery model, risks, and measurable business outcomes.
• Demonstrated experience adopting AI and GenAI for Software Testing and Quality Assurance, with a strong focus on identifying practical, high-value use cases that improve automation productivity, coverage, execution efficiency, maintenance, defect detection, and engineering effectiveness.
• Mandatory hands-on experience with AI-assisted, Agentic, or MCP-based Testing — including evaluating, designing, building, or implementing AI agents and frameworks for test generation, automation code generation, test execution, test maintenance, intelligent test selection, failure analysis, and test-result interpretation. Ability to establish responsible AI adoption by evaluating solutions against criteria of accuracy, reliability, maintainability, security, governance, and appropriate human oversight.
• Ability to define and drive enterprise-wide automation roadmaps, technology adoption strategies, and testing innovation initiatives — including AI and agentic testing — aligned with organisational objectives and measurable business outcomes.
• Experience establishing quality governance frameworks, metrics, KPIs, dashboards, and reporting structures to provide leadership visibility into quality, delivery performance, and engineering outcomes.
• Extensive experience in client engagement, stakeholder management, and executive communication — with the ability to influence decision-making, manage expectations, and build long-term client relationships across business, technology, architecture, development, DevOps, and delivery stakeholders.
• Proven ability to lead large, distributed, and cross-functional testing teams, fostering a culture of innovation, accountability, and engineering excellence.
• Strong understanding of Agile, DevOps, Continuous Integration, Continuous Delivery, Shift-Left, Shift-Right, and Continuous Testing practices, with experience embedding quality throughout the software development lifecycle

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