Application Guide

How to Apply for AI Engineer - Developer Experience

at Kaluza

🏢 About Kaluza

Kaluza is unique as a technology company specifically focused on decarbonising the energy sector through intelligent software, directly tackling climate change. They empower energy suppliers with cutting-edge platforms, offering the chance to work on meaningful technology with real-world environmental impact. Their focus on AI-driven solutions in a critical infrastructure sector makes them a compelling choice for engineers wanting purpose-driven work.

About This Role

This AI Engineer - Developer Experience role is central to enhancing how Kaluza's engineering teams build software using AI tools. You'll be responsible for integrating next-gen AI coding assistants (like Claude Code), establishing standards for agentic workflows, and measuring the impact of AI on development velocity and quality. Your work directly shapes developer productivity and safety while scaling AI usage across the company's decarbonisation mission.

💡 A Day in the Life

A typical day might involve collaborating with engineering teams to troubleshoot Claude Code integrations, designing new MCP server approval workflows, and updating agents.md standards based on team feedback. You could spend time analyzing AI Impact Metrics dashboards, then work with security teams to refine guidelines before documenting a new 'Golden Path' example for spec-driven development.

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🎯 Who Kaluza Is Looking For

  • Has hands-on experience deploying AI tools (e.g., Claude, GitHub Copilot, Cursor) in production engineering environments, not just personal projects
  • Understands the full 'LLM-ops' lifecycle including prompt management, cost tracking, security considerations, and integration with existing CI/CD pipelines
  • Can design scalable infrastructure for AI tooling, specifically with AWS and protocols like MCP (Model Context Protocol), ensuring reliability and low latency
  • Is a systems thinker who can balance innovation with governance—creating 'Golden Path' examples while implementing security guidelines for safe AI adoption

📝 Tips for Applying to Kaluza

1

Highlight specific examples where you've integrated AI coding tools (Claude Code, Copilot, etc.) into team workflows and measured their impact on PR velocity or code quality

2

Demonstrate your AWS production experience with concrete examples of deploying and scaling AI services, mentioning specific services like Lambda, SageMaker, or Bedrock if relevant

3

Show your understanding of developer experience by discussing how you've created onboarding materials, documentation, or standards for tool adoption in past roles

4

Research and mention Kaluza's energy sector focus—explain how your AI/developer experience skills could accelerate their decarbonisation mission

5

Prepare to discuss MCP (Model Context Protocol) and how you'd design a registry for AI tools—even if you haven't used it directly, show your understanding of similar protocol-based systems

✉️ What to Emphasize in Your Cover Letter

["Your experience with production AI systems, specifically how you've managed the lifecycle of AI tools in engineering teams", 'Examples of creating developer enablement materials (documentation, standards, onboarding guides) for AI tool adoption', "How you've balanced innovation with security and cost optimization when implementing AI solutions", 'Your interest in applying AI/developer experience skills to the energy/decarbonisation sector specifically']

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🔍 Research Before Applying

To stand out, make sure you've researched:

  • → Kaluza's specific products and platforms for energy suppliers—understand how their software enables decarbonisation
  • → Their parent company OVO Energy and their broader climate commitments (net-zero goals, etc.)
  • → Recent news about Kaluza's AI/technology initiatives—check their blog, press releases, or LinkedIn for updates
  • → The energy sector's digital transformation challenges and how AI is being applied to grid management, customer solutions, or renewable integration

💬 Prepare for These Interview Topics

Based on this role, you may be asked about:

1 Walk us through how you would design and implement an MCP registry for AI tools, including security approval processes and scalability considerations
2 How would you measure and track 'AI Impact Metrics'—specifically AI-generated contributions in PRs and their correlation to code quality?
3 Describe your experience with 'agentic workflows'—how have you standardized coding styles or automated architectural tasks using AI agents?
4 How would you approach creating 'Golden Path' examples for engineers to safely leverage AI tools while maintaining security standards?
5 What strategies would you use to evangelize 'Build Your Own' AI solutions and spec-driven development across engineering teams?
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⚠️ Common Mistakes to Avoid

  • Focusing only on AI model training/research without demonstrating experience integrating AI tools into developer workflows
  • Treating this as a generic AI engineering role without addressing the specific developer experience and enablement aspects
  • Neglecting to discuss security, cost, or governance considerations when implementing AI at scale

📅 Application Timeline

This position is open until filled. However, we recommend applying as soon as possible as roles at mission-driven organizations tend to fill quickly.

Typical hiring timeline:

1

Application Review

1-2 weeks

2

Initial Screening

Phone call or written assessment

3

Interviews

1-2 rounds, usually virtual

✓

Offer

Congratulations!

Ready to Apply?

Good luck with your application to Kaluza!

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