Raisin

platform engineer for internal AI platforms

In short

Senior platform engineer role at Raisin's AI Enablement team, building and operating an internal AI platform that gives engineering teams governed, secure access to AI models, tools, and agentic workflows. The job spans backend/infrastructure work (IaC, observability, CI/CD) and hands-on LLM tooling (gateways, MCP, guardrails, usage limits), requiring 5+ years of backend/platform engineering experience and practical LLM API experience beyond experimentation. Hybrid role based in Berlin at a fintech connecting savers with banks across the EU, UK and US.

About
Raisin is a platform for savings and investment products that connects consumers with banks in the EU, the UK, and the US. Its AI Enablement team builds an internal AI platform that gives teams governed access to AI models and tools, with controls for data security, auditability, reliability, and cost efficiency.
Responsibilities
•Build and operate shared services that provide governed access to AI models and tools, including authentication, provider routing, 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 platform services in production using infrastructure as code, observability, 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, including agent instructions, skills, and integrations with engineering systems
•Help engineering teams adopt AI-assisted development, improve quality and speed, and measure its 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 the data to decide what to build next
•Lead the design of new capabilities from idea to production, including build-versus-buy decisions, and document the rationale
•Work with security, legal, and compliance colleagues to turn requirements into automatically enforced platform controls
•Make model choices based on cost, latency, and quality
•Support other engineers through design reviews, pairing, and knowledge sharing
Requirements
•5+ years as a software engineer in backend, platform, or infrastructure roles, including production systems used by other teams
•Experience building platforms, developer tooling, or shared services for internal customers
•Strong skills in at least one programming language
•Solid cloud and delivery fundamentals, including AWS or another major cloud, containers, infrastructure as code, and CI/CD
•Practical experience with LLM APIs or AI tooling beyond experiments
•Use AI coding assistants in daily work
•Comfortable with evolving scope, pragmatic trade-offs, and explaining decisions clearly to technical and non-technical colleagues
Nice to have
Python, TypeScript or JVM languages, LLM gateways, Model Context Protocol (MCP), managed model services, agent runtimes, AI-assisted development workflows for other engineers, OAuth 2.0 / OIDC, SSO, role-based access control, delegated access, API gateways, rate limiting, multi-tenant isolation, observability such as OpenTelemetry, and understanding model cost, latency, and quality trade-offs
Benefits
•Employee Development Budget of €2,000 and four full training days per year
•Flexible working hours and 30 vacation days
•Company pension scheme supported with 20%
•Urban Sports Club membership subsidized with more than €20 per month
•Deutschland Ticket subsidized with €25 per month
•JobRad bike leasing, tax savings, and monthly insurance costs covered by Raisin
•Snacks, fresh fruit, and drinks provided at the office
•Relocation support may be available

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