Lead Quality Engineer – Test Automation, Transformation

8 West Consulting

. Assess testing maturity across enterprise teams, prioritise common opportunities and lead phased adoption of automation, AI-assisted testing and improved data practices .

Posted 11/11/2026full-timeRemote • IrelandSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in quality engineering principles, AI-assisted testing, and automation across enterprise environments, with a strong focus on reusable test data management and effective communication with stakeholders. Proven ability to lead testing improvements, mentor engineers, and implement robust testing frameworks and practices.

Highest-signal resume keywords

AI-Assisted Testing ImplementationC# ProgrammingSQL Database ManagementTest Automation FrameworksCI/CD Integration

ATS Keywords

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Hard Skills

CodingDebuggingAutomationTest DesignData GenerationTest ReportingRegression TestingDefect InvestigationTest Stability MeasurementSynthetic Data Creation

Soft Skills

MentoringInfluencing Without AuthorityClear CommunicationStakeholder EngagementCollaboration

Tools & Technologies

PlaywrightSeleniumCypressPostmanAzure DevOpsGitCI/CD PipelinesTest EnvironmentsFixturesBuilders

Industry Keywords

Enterprise TestingQuality EngineeringRegulated EnvironmentsAI Quality PracticesConsultancy Experience

Tech Stack

Tools & technologies

AzureCypressJavaJavaScriptPythonSeleniumSQLTypeScript.NET

About the role

Key responsibilities & impact

Assess testing maturity across enterprise teams, prioritise common opportunities and lead phased adoption of automation, AI-assisted testing and improved data practices
Write and debug UI, API, integration and data tests
Investigate defects and support releases on live engagements
Define quality engineering principles, review solutions and guide tool choices across projects
Design and implement reusable test-data builders, fixtures, seeding and reset patterns
Implement AI-assisted test design, case and script generation, synthetic data creation and failure analysis
Establish validation, safe-use practices and repeatable adoption for AI-enabled testing
Establish lightweight patterns for frameworks, CI/CD, test reporting and governance
Pair with testers and developers, review implementations, mentor senior engineers and build training and adoption plans
Explain quality risks, investment choices, technical trade-offs and transformation progress to senior stakeholders and clients
Measure adoption and results across projects, including regression effort, test stability, independent data setup, AI effectiveness, feedback speed and release confidence

Requirements

What you’ll need

Personally led substantial testing improvements across several teams, applications or workstreams in an enterprise environment, with clear evidence of adoption and delivery outcomes
Strong coding, debugging and automation skills, including direct work on production test suites in C#, TypeScript/JavaScript, Python, Java or equivalent
Implemented AI-assisted testing on real enterprise projects and helped other engineers adopt it, with verified test/data generation, practical safeguards and measured results
Personally built reusable, isolated test datasets and shared patterns for relational or integrated systems using SQL, APIs, fixtures and builders; manages integrity, synthetic/masked data and reset
Able to set patterns across UI, API, integration, contract, data and regression tests, review designs and balance reuse with project-specific needs
Practical experience testing .NET, SQL Server and/or Azure applications, including Azure DevOps or equivalent pipelines, Git and engineering workflows
Broad experience with Playwright, Selenium, Cypress, Postman or equivalents, plus CI/CD integration, test environments and flaky-test diagnosis
Built practical roadmaps, gained support across teams and delivered improvements incrementally despite competing deadlines and legacy constraints
Can influence engineering and business leaders without formal authority, explain investment and quality trade-offs, and develop engineers through pairing and mentoring
Desirable: regulated enterprise environments, advanced AI quality practices, specialist testing, broader platforms and consultancy experience
Ability to communicate clearly with colleagues, clients and senior stakeholders, including speaking English

Benefits

Comp & perks

Remote work arrangement
Opportunities to work across US, European and UK client engagements
Professional coaching, mentoring and practical training opportunities
Opportunities to work with AI-assisted testing and modern quality engineering practices