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Pre-Sales Senior Engineer
Kaluza
London, GBR
Full-time
Senior
Hybrid
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Location
- London/Bristol - Hybrid
- Team: Commercial
- Reporting To: Head of Client Solutions
- This role is based in London or Bristol and requires existing right to work in the UK. At this time, we are not able to offer visa sponsorship for this role. We are committed to building a diverse, global team and our sponsorship policy is evaluated on a role-by-role basis. We encourage you to keep an eye on our careers site to stay informed about future opportunities where we are able to offer visa sponsorship.
- 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. Leveraging Data, AI, and real-time decision-making we turn energy complexity into growth opportunities for our partners.
- By combining predictive algorithms with human-centred design, Kaluza makes clean energy dependable and affordable.
- 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 will I be doing?
As a Senior Pre-Sales Engineer , you are a "developer-plus" technical contributor. You are responsible for building high-quality mock backends, APIs, and demo infrastructure, but with a unique twist: you leverage LLMs and Generative AI to prototype at high velocity.
This role sits at the critical boundary between Product Engineering and Go-to-Market. While you won't build production systems, you will build "production-shaped" assets: reusable, well-structured, and documented services that enable credible technical storytelling and high-fidelity client validation.
Your core responsibilities will include:
AI-Accelerated Prototyping: Leverage LLMs (e.g., Claude and Gemini) to rapidly scaffold, build, and iterate on proof-of-concept apps and mock services. You move faster than a traditional sprint by using AI to handle the "heavy lifting" of boilerplate and logic generation.
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