Director, Quality & Release Engineering

Own and evolve the quality strategy across delivery streams, aligned to programme objectives and client SLAs

Define and maintain release governance frameworks — release readiness criteria, risk acceptance, and sign-off authorities

Set quality standards and coverage expectations; ensure QA leads translate these into domain-level test strategies

Drive defect governance at programme level — internal and client-facing SLA compliance

Represent quality and risk in senior leadership, architecture, and product forums

Directly manage a team of engineers building and maintaining bespoke automation tooling, leveraging AI and LLM capabilities

Own the test data management strategy — including AI-assisted synthetic data generation and environment data integrity

Evaluate and select off-the-shelf AI testing tools; define governance frameworks for their use and validation

Ensure governance gates are maintained as AI participation in the PDLC grows — accountable humans must remain in the loop for risk acceptance and production judgement

Establish tooling standards that QA leads can adopt across domains without creating dependency on a central bottleneck

Lead, develop, and performance-manage QA leads embedded across domains; define the operating model and career framework for the function

Own the accountability split clearly: QA leads own test strategy and tooling choices for their domain; this role owns the standard they work to

Drive consistency across streams without becoming a handoff point — enable QA leads to move fast within well-defined guardrails

Build a quality engineering culture — not a bug-finding one

Lead the transformation of QA practice from script maintenance to intelligent, risk-based, AI-assisted quality engineering

Drive upskilling across the function — building capability in AI tooling, context engineering, and agent-assisted workflows

Manage resistance and build confidence in new ways of working; bring the team through change without losing them

Communicate quality outcomes in business terms to senior stakeholders — escaped defect rates, release stability, risk posture

Own the release quality process end-to-end: environment strategy, regression coverage, go/no-go decisions, and post-release monitoring

Embed shift-left practices — quality gates early in the PDLC, not just at release

Manage the tension between delivery velocity and release stability, particularly as AI-generated code volumes increase

About You Ideally you’ll have/be

Proven track record leading a QA or quality engineering function of significant scale — including embedded domain leads and direct management of practitioners

Has directly managed engineers building tooling or automation infrastructure — not just managed QA practitioners executing test plans

Has delivered a meaningful QA transformation: AI adoption, automation maturity uplift, defect governance overhaul, or similar

Has worked in a multi-client or multi-product platform environment, managing quality outcomes across concurrent delivery streams

Has owned release governance in a complex, multi-stream delivery context — including go/no-go accountability

Exposure to energy, utilities, billing, or similarly regulated complex domains is a plus — not essential Strong grounding in test strategy, automation frameworks, and CI/CD integration — sufficient to credibly lead engineers building these things

Working knowledge of LLMs and AI tooling in a QA context: test generation, defect triage, coverage analysis, synthetic test data

Understands test data management principles and the challenges of environment data integrity at scale

Able to evaluate build vs. buy for tooling; assess AI testing platforms with appropriate scepticism Comfortable setting strategy and being accountable for outcomes — not just owning process

Able to operate at programme level with senior engineering and product stakeholders

Experienced in leading distributed, multi-timezone quality functions

Strong communicator — translates quality metrics into business outcomes; can make the case for investment in tooling and governance Demonstrated experience leading practice transformation in an engineering context

Able to bring people with them through transitions that challenge established ways of working

Comfortable with ambiguity; can hold direction steady while the detail is still being worked out

Familiar with observability, production monitoring, and shift-right quality practices

Where you'll work We offer flexible working, with an expectation of 3 days a week in the office. This gives us the best of both: real time together to collaborate and build relationships, with the flexibility to work in the way that suits you best the rest of the week.

Kaluza Values Here at Kaluza we have five core values that guide us as a business: Play to win, Solve the real problem, Build trust every day, Own the outcome, Go further together.