Загрузи резюме, чтобы видеть мэтчи с вакансиейЗагрузи резюме, чтобы видеть мэтч с вакой
подготовься к отклику
ai-инструменты
Чтобы адаптировать резюме под вакансию или составить сопроводительное письмо, загрузи резюме
описание
Are you ready to commit 2 days per week in our Berlin office?
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.
задачи
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
требования
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
Будет плюсом: 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
условия
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
