Location: London or Bristol, UK (hybrid, three days a week in the office)
Level: Director
Team: Quality & Release
Salary: £150,000 - £180,000 + discretionary bonus
Contract: Permanent
Reporting To: VP Engineering
Please note: This role requires an existing right to work inthe UK. We can’t offer visa sponsorship, but we review sponsorship role by role, so keep an eye on our careers site for future opportunities.
About Kaluza
Kaluza is the Energy Intelligence Platform, turning energy complexity into seamless coordination. We help energy companies overcome today’s challenges while accelerating the shift to a clean, electrified future.
Our platform orchestrates millions of real-time decisions across homes, devices, markets and grids. By combining predictive algorithms with human-centred design, Kaluza makes clean energy dependable, affordable and adaptive to everyday life.
With teams across Europe, Asia and Australia, and a joint venture with Mitsubishi Corporation in Japan, we power leading companies including OVO, AGL and ENGIE, as well as innovators like Volvo and Volkswagen.
What you’ll do
The quality engineering function is shifting from manual oversight and process governance toward an AI-assisted product development lifecycle where QA leads its own domain test strategy and bespoke tooling drives automation maturity. This role will drive this shift in our organization and ways of working.
You will own quality and release governance at programme level, directly manage an engineering team building AI-assisted automation and test data capability, and set the standard that QA leads across delivery streams work to. You will be as comfortable driving change as you are accountable for outcomes. Responsibilities will include:
Strategic Quality Leadership
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
AI-Driven Tooling & Automation
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
QA Function Leadership & Operating Model
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
Change Management & Adoption
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
Release Management
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
What you’ll bring
Ideally, you’ll have:
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 thingsWorking 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 processAble 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 contextAble 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
Our Values
Five values guide how we work at Kaluza:
Play to win: Collective pride in decarbonising energy at scale.
Solve the real problem: Cutting through complexity to focus on real-world outcomes.
Build trust every day: Consistency, transparency and doing what we say.
Own the outcome: Full accountability, wins and setbacks, without ego.
Go further together: Collaboration, respect and different perspectives.
Our Perks
Time off and family: 26 days’ holiday, plus 26 weeks’ full pay for new parents with no qualifying service period
Health and security: Private medical insurance with virtual GP, life assurance, pension scheme, free mortgage advice and eye tests
Pay and flexibility: Discretionary bonus, a Flex Fund of 5% [of salary] to spend on the benefits you want most, retail discounts through Perks at Work
Growth and setup: Personal learning budget, home office budget
Climate: Furthr, our climate action app
Come as you are
We want to meet people from all walks of life. The more inclusive we are, the better our work will be, and we recognise talent on merit and potential. If you’re excited about the role but don’t tick every box, we’d still love to hear from you.
Find out more on our careers page and LinkedIn. Our Applicant Data Protection Policy is here.
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