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Senior Engineer I - AI Developer Experience
Senior Engineer I - AI Developer Experience
Kaluza is seeking a Senior Engineer I to architect and evolve their Internal AI Engineering Platform. This role involves building infrastructure, tooling, and workflows for AI-enabled development, with a focus on enhancing developer productivity, system reliability, and security. The ideal candidate will have experience with production-grade AI systems, distributed systems, AWS, and a passion for developer experience.
About the role
About the Role
In this role, you’ll play a pivotal role in architecting and evolving our Internal AI Engineering Platform. You'll be building the infrastructure, from Model Context Protocol (MCP) servers to shared workflows, that help our software teams move faster while keeping systems reliable and secure. Your work will directly influence how Kaluza reduces defects, scales productivity, and sets a high standard for AI-enabled development.
What you will be doing?
- AI Tooling Orchestration: Lead the trials and deployment of next-generation engineering tools, including Claude Code, Kiro, and Opencode, ensuring they integrate seamlessly into the developer inner loop.
- Infrastructure & Connectivity: Design and maintain our MCP (Model Context Protocol) registry, establishing a secure and scalable process for approving and deploying new servers and tools.
- Shared Workflows: Develop and maintain shared services and standards that help standardize coding practices and automate repetitive architectural tasks across teams to facilitate AI workflows.
- Spec-Driven Development: Build and evangelize "Build Your Own" AI solutions and low-code automations that support spec-driven development, reducing the gap between requirements and production code.
- Enablement & Governance: Author high-quality onboarding documentation, security guidelines, and "Golden Path" examples that help engineers leverage AI safely and effectively.
- Performance Analytics: Architect and automate the tracking of AI Impact Metrics, specifically focusing on the volume of AI-generated contributions within PRs and their correlation to code quality and velocity.
About You
Ideally you'll have/be:
- Production-Grade AI Implementation: Experience building and running production systems with a deep curiosity about the "LLM-ops" lifecycle and integrated agentic workflows.
- Systems Thinker: Solid foundational knowledge of distributed systems and how to integrate third-party AI APIs (like Claude or OpenAI) without compromising reliability.
- Infrastructure as Code & Beyond: Hands-on experience with AWS in production, treating AI prompts and MCP configurations with the same version-control rigor as infrastructure.
- The DevEx Mindset: A passion for developer productivity, building experiences that make an engineer's day-to-day life easier and more creative.
- Security & Governance First: Ability to design approval processes and security guardrails that protect the business from risks like data leakage or prompt injection.
What will set you apart:
- Data-Informed Approach: You enjoy defining and automating metrics, such as tracking AI-generated code volume, to prove the value of the tools you deploy.
- Collaborative Communicator: Ability to translate complex AI concepts into clear guides and onboarding docs for the wider engineering community.
- Relentless Curiosity: A motivation to continuously trial new tools in a weekly-changing landscape and the agility to pivot when better solutions emerge.