Location: Bristol or London
Level: C2
Team: Quality Enablement
Contract: Permanent
Please note: This role requires an existing right to work in the UK. We can’t offer visa sponsorship, but we rev
Kaluza Overview
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, North America, 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.
The role
Kaluza has new opportunities for QA Developer Engineers who will build and maintain automation frameworks that test AI-generated and AI-assisted code, and develop agent-based tooling that supports engineering teams across the business. These roles sit at the intersection of software development, quality engineering, and applied AI — you will build the tools that other engineers and clients rely on to develop, test, and ship AI-driven solutions with confidence.
The QA Development Engineers will be part of a Quality Enablement function which forms part of Kaluza’s Quality departments.
They will work closely with Applied Engineering and Global Products teams to deliver reusable frameworks and agent solutions. You will have opportunities to work with internal and external clients to understand their requirements and build solutions to meet their needs. AI will be a core part of your own workflow — used to accelerate
the design, build, and iteration of testing tools and frameworks.
What you will be doing
Automation Framework Development: build and maintain automation frameworks specifically for testing AI-generated code and AI system outputs, ensuring accuracy, reliability, and consistency.
Agent Solution Development: Create agent-based tools and solutions that Applied Engineering and Global Products teams can use to deliver work faster, and that developers can use to test their code and systems.
AI-Assisted Tool Building: Use AI tools and techniques to build, refine, and scale internal testing tools and frameworks efficiently, embedding AI into your own development lifecycle.
Solution-Driven Delivery: Operate as part of a solution-focused team, translating customer and stakeholder requirements into working tools, frameworks, and processes.
Continuous Improvement: collaborate with other team members to identify bottlenecks in code and architecture, and build internal AI-driven tools to accelerate our test-and-deploy lifecycles. participate in constructive code reviews to champion best engineering practices and maintain high code quality.
Cross-Team Collaboration: Partner with internal engineering teams (as internal customers) to understand their AI deployment constraints and testing needs — gathering requirements and delivering quality frameworks and solutions that meet real needs.
Documentation and Enablement: Produce documentation and guidance so that developers, QA teams, and clients can adopt and use the frameworks and agent tools effectively.
Feature Delivery and Ownership: Take technical ownership of discrete components and features end-to-end, writing clean, well-tested code.
What you will have
Proven experience as a QA Engineer, Automation Engineer, or Software Engineer with a strong quality/testing focus.
Hands-on experience building test automation frameworks (e.g. using tools/languages such as Python, JavaScript/TypeScript, Java, Selenium, Playwright, Cypress, or similar).
Experience working with or testing AI-generated code, AI models, or AI agents — covering both deterministic validation (is the generated code correct) and non-deterministic evaluation (is the AI's behavior/output acceptable).
Understanding of software development lifecycle (SDLC) and QA methodologies.
Problem-solving skills with a solution-oriented mindset.
Excellent communication skills, able to explain technical concepts to both technical and non-technical audiences.
What will set you apart:
Experience building or integrating AI agents (e.g. LangChain, AutoGen, custom agent frameworks, MCP-based tooling).
Understanding of prompt engineering and LLM evaluation techniques (e.g. faithfulness, relevance, LLM-as-a-judge patterns), since traditional pass/fail assertions don't translate well to AI agent testing.
Familiarity with CI/CD pipelines and integrating automated testing into deployment workflows.
Experience with API testing.
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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