The posting, in Wayve's own words
archived Oct 5, 2026Before the detail, here's the challenge you'd help us solve. We build the embodied intelligence that moves real vehicles safely, and the ecosystem a billion machines will run on in the future. Very few people in AI can say this. Every role here, whatever the team, plugs into that. Here’s what this particular role covers. 🛠️ About our Engineering Teams Wayve’s AI Enablement team builds the shared platforms that help people across the company use language models and AI agents safely, reliably, and cost-effectively. As an early member of this platform team, you’ll help shape both the technical foundations and the standards for how AI-powered tools are built and operated across Wayve. 🧠 Your day-to-day You’ll design, build, and operate infrastructure for model access, agent runtimes, and observability. You’ll take projects from initial problem definition through technical design, deployment, and ongoing operation, partnering closely with security, IT, and engineering teams. You’ll also support teams adopting the platform by troubleshooting issues, documenting reusable patterns, and helping people understand what’s possible with the tools available. 🧩 What you’ll be working on A governed, production-ready access layer for language models, including routing, authentication, cost controls, and auditability. Secure infrastructure and reusable tooling for running agentic workflows in production. Observability covering platform usage, cost, reliability, and performance. Governance and safety controls that make AI use secure, compliant, and auditable. Shared primitives, standards, and best practices that enable teams to build and deploy agents without creating one-off infrastructure. Reliable, scalable deployments using cloud infrastructure, Kubernetes, and infrastructure-as-code. 🙌 You should apply if You have strong software engineering experience building APIs, services, or developer tooling. You’ve built or operated platforms and infrastructure used by other engineering teams. You have hands-on experience with cloud infrastructure, Kubernetes, and infrastructure-as-code. You’re familiar with LLM APIs and the surrounding ecosystem, such as model gateways, agent frameworks, MCP, or RAG. You understand production observability, including metrics, tracing, and logging. You take a security-conscious approach to authentication, authorization, governance, and auditability. You’re comfortable taking ownership in an ambiguous, fast-moving environment and can communicate clearly through documentation and collaboration. 🌱 Not ticking every box? That’s totally okay! If you’re passionate about autonomy and keen to learn, we encourage you to apply even if you don’t meet every requirement.