tem
Staff QA Automation Engineer

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📈 Who We Are:
We are rebuilding the energy transaction, making it transparent and fair. Our goal is to put power back where it belongs, in the hands of customers and to take on one of the most critical problems of our century, access to low-cost electricity.
Our team exists to fix a broken global energy market that's long favoured legacy operators, intermediaries, and opaque pricing. Today's electricity system was not designed for rapid decarbonization, AI-driven efficiency, or fair access for the actual users - businesses and generators.
We've built the first AI-native transaction infrastructure to reinvent how electricity is bought, sold, and priced. Our technology is designed to cut out the inefficient fees, automate complex market flows, and bring transparency and fairness to energy transactions at scale.
In late 2025, after extraordinary growth, we closed a $75 million Series B - led by Lightspeed Venture Partners with participation from Albion, Atomico, Allianz, Hitachi Ventures, Hitachi Ventures, Schroders Capital, and others - positioning us for global expansion, deeper product innovation, and category leadership.
We're scaling internationally and building toward a future where AI-driven infrastructure is foundational to electricity markets worldwide. Since launch, our modern utility product, known as RED, has already facilitated thousands of business customers and billions in energy transaction value, proving that modern software and AI can transform an industry built on legacy systems.
At tem, we're not just building another energy company; we're rearchitecting market infrastructure so that transparency, efficiency, and sustainability become the default, not the exception.
The Role
We're hiring a Staff QA Automation Engineer to help shape how quality engineering works across tem.
QA sits inside Platform, a central team that builds the tooling and standards the rest of engineering runs on. You'll design the frameworks and practices that let them test well themselves, and scale into the future. As we scale, you'll lead and develop scripts that equip engineering teams with the automation and standards to own quality themselves.
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
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Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
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Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
Only hits
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The product is built on a microservice architecture that brings real complexity to testing. You'll own the quality engineering approach as the organization scales — setting the standards, building the tooling, and driving adoption across engineering.
What you'll work on:
- A risk-aware CI testing standard any team can run: a dependency model that drives test selection and breaking-change detection, so most PRs get a fast targeted run with a clear confidence signal at the point of change.
- Unit, integration, and contract testing standards with an observability layer that keeps pipelines honest and not flaky. Proven through reference test suites in real service repos, not a QA-authored checklist.
- The quality side of canary releases: working with the wider Platform team to define automated pass/fail analysis against production traffic so deployments promote or roll back without manual sign-off.
- AI in the quality pipeline: LLM-based change-risk classification, targeted mutation testing, test generation, and self-healing checks. We already use LLM tooling across QA and want someone to take it further.
You report to Bartek Kucharski (QA). Specialist individual contributor, no direct reports.
Requirements
Must haves:
- Expertise in test automation frameworks including pytest, Playwright, Selenium, and API testing or similar.
- Experience architecting and maintaining test automation frameworks and tooling used across a wider engineering organization.
- Deep knowledge of testing across microservice or distributed systems, including API-level automation, CI/CD integration, and service-level testing strategies.
- Experience leading innovation and PoCs in testing, particularly AI-led regression optimization and change-risk analysis.
- Strong collaboration and delivery focus across multi-project environments and distributed teams.
- Contract testing or consumer/provider verification (Pact, OpenAPI schema validation, or similar).
- AWS infrastructure experience (Lambda, GitHub Actions self-hosted runners, deployment tooling).


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Nice to have:
- Progressive deployment experience: canary releases, feature flags, automated rollback from production signals.
- Mutation testing, whether traditional tooling or LLM-based.
- Test-data management and environment-isolation strategy in shared environments.
- Experience in a regulated or high-stakes domain (energy, fintech, payments).
Benefits & Perks
Our current band for this role is £104,000 or equivalent in local currency. We pay against a clear benchmark for your role and level. No fixed once- or twice-a-year cycle - pay moves when the evidence for it does.
- Stock options so everyone has ownership in our mission.
- 25 days holiday plus public holidays. Swap public holidays for the ones that matter most to you, and enjoy your birthday off.
- Remote first and flexible working, with clear core hours and no internal meetings on Friday afternoons.
- Home working and wellbeing budgets.
Interview Process
We move fast. Most processes take 2 to 3 weeks from the first chat to offer. If you need us to adapt anything, let us know.
- Intro call with Talent, 30 minutes.
- Behavioural Interview with the Hiring Manager, 60 minutes.
- Skills interview with cross-functional leaders, 90 - 120 minutes, including a practical exercise on framework design and AI-in-test.
- Bar Raiser interview with leadership stakeholders, 45 minutes.
We welcome applications from people of all backgrounds, experiences, and identities, including those that are traditionally underrepresented in the tech and energy sectors. If you're excited about this role but not sure you meet every requirement, we'd still love to hear from you. Your unique perspective could be exactly what we're looking for.
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