Director, Quality & Release Engineering

Overview

In this role you will lead a Quality Engineering function at scale, steering AI-assisted automation and test data capability to improve delivery quality. You will own programme-level quality and release governance, aligning with client SLAs and strategic objectives. You’ll drive a transformation from manual QA to risk-based, AI-enabled practices and build a cross-domain QA operating model. The position offers the chance to shape tooling standards, governance, and a high-impact quality culture across multiple streams.

Pay / Benefits

• Pension Scheme
• Discretionary Bonus Scheme
• Private Medical Insurance + Virtual GP
• Life Assurance
• 26 days holiday
• Personal Learning Budget

Responsibilities

• Shape and evolve the overall quality strategy across delivery streams to meet objectives and SLAs
• Define and maintain release governance with readiness criteria, risk acceptance, and sign-off authority
• Lead and codify standard domain-level test strategies and coverage expectations for QA leads
• Govern defect management at programme level, ensuring SLA compliance for internal and client-facing metrics
• Lead a team of engineers building bespoke automation tooling using AI and LLM capabilities
• Own test data management strategy, including AI-assisted synthetic data and environment data integrity
• Evaluate and select off-the-shelf AI testing tools and establish governance for their use
• Maintain governance gates as AI participation in PDLC grows, ensuring human accountability for risk decisions
• Set tooling standards across domains to avoid central bottlenecks
• Develop QA leads and define operating model and career framework for the function
• Drive change management to shift QA practices toward intelligent, risk-based quality engineering
• Upskill teams in AI tooling, context engineering, and agent-assisted workflows
• Communicate quality outcomes in business terms to senior stakeholders
• Own end-to-end release quality processes, including environment strategy, regression coverage, go/no-go decisions, and post-release monitoring
• Embed shift-left quality gates and balance delivery velocity with release stability

Key requirements

• Proven leadership of a QA or quality engineering function at significant scale with embedded domain leads
• Direct management of engineers building tooling or automation infrastructure
• Experience delivering a meaningful QA transformation (AI adoption, automation uplift, governance overhaul)
• Experience in multi-client or multi-product environments with quality outcomes across concurrent streams
• Ownership of release governance in complex multi-stream contexts (go/no-go accountability)
• Exposure to energy, utilities, billing, or similarly regulated domains is a plus
• Strong grounding in test strategy, automation frameworks, and CI/CD integration
• Working knowledge of LLMs and AI tooling in QA (test generation, defect triage, coverage)
• Understanding of test data management and environment data integrity at scale
• Ability to evaluate build vs. buy for tooling and assess AI testing platforms
• Comfort with programme-level stakeholder communication and accountability
• Experience leading distributed, multi-timezone quality functions
• Strong communication skills translating quality metrics into business outcomes
• Experience leading practice transformation in engineering contexts
• Ability to lead through ambiguity and manage change

• Strong communication and storytelling to business leaders
• Change management and stakeholder alignment
• Collaborative leadership across domains and time zones
• AI tooling and LLM capabilities in QA
• Automation tooling development and maintenance
• Test data management and synthetic data generation

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