AI Platform Engineer

Who you are

• 5+ years as a software engineer in backend, platform, or infrastructure roles, including production systems that other teams depend on
• Experience building for internal customers: a platform, developer tooling, or shared services used by other engineers
• Strong skills in at least one programming language (Python preferred; TypeScript and JVM languages also relevant)
• Solid cloud and delivery fundamentals: AWS or another major cloud, containers, infrastructure as code, and CI/CD
• Practical experience with LLM APIs or AI tooling beyond experiments, and you use AI coding assistants in your daily work
• You are comfortable with evolving scope, make pragmatic trade-offs, and explain them clearly to technical and non-technical colleagues
• Experience with LLM gateways, the Model Context Protocol (MCP), managed model services, or agent runtimes
• You have rolled out AI-assisted development workflows for other engineers, such as agent instructions, reusable skills, or automated code review
• Identity and access: OAuth 2.0 / OIDC, SSO, role-based access control, or delegated access
• API gateways, rate limiting, multi-tenant isolation, or observability (OpenTelemetry or similar)
• A feel for the cost, latency, and quality trade-offs of different models
• You don't need to tick every box. If you have strong platform or developer-tooling experience and real curiosity about AI, we would like to hear from you

What the job involves

• AI Enablement builds Raisin's internal AI platform. We make it easy and safe for every team, from engineering and product to business operations, to use AI in their daily work and in the products they build
• We provide the shared foundation for that: governed access to AI models and tools, the controls that keep data secure and usage auditable, and the visibility teams need to run AI reliably and cost-effectively
• We also shape how Raisin builds software with AI, from AI-assisted coding to agentic workflows that support teams across the development lifecycle. Because Raisin operates in regulated financial services, security and compliance are core to how we design the platform
• You will join early and help shape how AI is used across Raisin
• As an AI Platform Engineer, you build and run the platform that lets teams use AI safely, and you help engineering teams bring AI into how they build software
• You own your work from the first design to production and work directly with the people who use it. You won't do all of the following at once: you will go deep in a few areas and contribute to the rest
• Design, build, and operate shared services that give teams governed access to AI models and tools, including authentication, routing across providers, usage limits, guardrails, and audit logging
• Build safe ways for AI agents to connect to internal systems and data, with clear identity, permissions, and review
• Run what you build in production: infrastructure as code, observability for reliability, usage, and cost, and incident response
• Design and build agentic workflows that support engineers across the development lifecycle, from planning and implementation to code review, testing, and release
• Create reusable building blocks for AI tools, such as agent instructions, skills, and integrations with engineering systems, that teams can adopt and extend
• Help engineering teams adopt AI-assisted development in a way that improves quality as well as speed, and measure the effect on delivery
• Work with engineers, product managers, and business teams to understand their needs and turn them into platform capabilities
• Make the platform and its tools easy to adopt through self-service, sensible defaults, and clear documentation
• Measure adoption, reliability, cost, and impact, and use that data to decide what to build next
• Lead the design of new capabilities from first idea to production, including build-versus-buy choices, and document decisions so others can follow the reasoning
• Work with security, legal, and compliance colleagues to turn their requirements into controls the platform enforces automatically
• Make principled model choices based on cost, latency, and quality
• Raise the bar for the engineers around you through design reviews, pairing, and sharing what you learn

Benefits

• Visa & Relocation Support
• 1,700 EUR Training Budget
• Free Choice of Hardware
• Beginner German Classes
• Food & Drinks
• Flexible working hours, home office and 28 vacation days
• Subsidised Urban Sports Club Membership
• Company Pension Scheme
• Team Events