Location: Berlin, Germany Category: Engineering Company: Raisin Employment Type: Full-time Posted: Recently listed on Arbeitnow
About the Company
Raisin is a fintech platform that connects everyday savers and investors with banks across the EU, UK, and US, giving people access to better interest rates while helping banks diversify how they raise funds. Founded in 2012, the company has grown into a genuinely global operation — more than 800 employees from 75+ countries, over €80 billion in customer assets, and more than one million investors on the platform who’ve collectively earned over €5 billion in returns. In short: this is an established, well-funded fintech, not an early-stage gamble.
The Role
Raisin is hiring an AI Engineer to join its AI Enablement team — the group responsible for rolling out AI capabilities across Raisin’s products and internal tools in a consistent, production-ready way. Rather than chasing AI trends for their own sake, this team builds shared foundations that other engineering teams can plug into safely and reliably.
As the AI Engineer, you’d sit at the intersection of hands-on engineering and cross-team guidance. Day to day, that looks like:
- Helping product and engineering teams adopt AI — spotting good use cases, advising on implementation trade-offs, and pushing for reusable patterns instead of one-off solutions.
- Building shared AI infrastructure — extending internal tools and services, defining patterns for integrating large language models, and keeping a lid on AI compute costs across teams.
- Guiding technical decisions — evaluating platforms and tools with an eye on security, scalability, and whether AI is even the right answer for a given problem.
- Keeping things safe and efficient — balancing model choice against cost, latency, and token usage, while working with Security and Legal on responsible-use safeguards.
What Raisin Is Looking For
This isn’t an entry-level opening. Ideal candidates bring:
- 5+ years of software engineering experience, ideally backend or platform-focused
- Comfort working as a generalist across different technical domains and evolving priorities
- Strong Python skills (JVM languages are also welcome), plus solid experience with distributed systems, APIs, and cloud platforms — AWS preferred
- Real, hands-on experience with AI tools or LLM APIs, including concepts like prompt design, context engineering, and retrieval-based approaches
- Good judgment about when AI is the right tool — and when it isn’t
What’s in It for You
Raisin backs the role with a solid benefits package for Berlin standards:
- €2,000 annual learning budget plus four dedicated training days a year
- Flexible hours, home office options, and 30 vacation days
- Company pension scheme, with Raisin covering 20% of contributions
- Subsidies for Urban Sports Club, the Deutschland Ticket, and JobRad bike leasing
- Office snacks, fresh fruit, and drinks
- Relocation support if you’re moving from another city or country
Why This Role Stands Out in the Current Market
AI Engineer openings are everywhere right now, but a lot of them boil down to “wire up an API call to a chatbot and call it a day.” This one is different in an important way: it’s an enablement role, not a single-product role. Instead of owning one AI feature, you’re helping define how an entire engineering organization approaches AI — which is a much bigger scope of influence, and a much better résumé line, than most AI job titles floating around today.
It also sits in a genuinely regulated industry. Fintech companies can’t just bolt an LLM onto a workflow and ship it; every integration has to hold up against security reviews, data-privacy rules, and financial compliance requirements. That makes the role more demanding, but it also means the skills you build here — cost-aware model selection, safe integration patterns, working alongside Security and Legal — transfer well to any serious enterprise AI job afterward.
What a Typical Week Might Look Like
Roles like this tend to blend a few different modes of work rather than a single repetitive task list:
- Discovery conversations with product or engineering teams who have an idea but aren’t sure whether AI is the right tool, or how to implement it safely
- Deep technical work on shared infrastructure — think internal libraries, retrieval pipelines, or LLM-gateway services other teams can plug into
- Cost and performance tuning, since running LLMs at scale gets expensive fast if nobody’s watching token usage or model choice
- Documentation and internal advocacy, making sure the patterns you build actually get adopted instead of every team reinventing its own approach
If you enjoy being the engineer other engineers come to for advice — not just writing code in isolation — this kind of cross-functional, advisory-plus-hands-on mix is usually a good sign you’ll enjoy the day-to-day.
Berlin as a Base for This Kind of Career
Berlin has become one of Europe’s strongest fintech hubs over the past decade, home to a dense cluster of banks, payment startups, and companies like Raisin that sit right at the intersection of finance and technology. For an AI Engineer specifically, that matters: the city has a deep pool of peers working on similar regulated-AI problems, a strong meetup and conference scene, and a relatively high concentration of English-speaking tech roles, which lowers the barrier for engineers relocating from abroad. Combined with Raisin’s relocation support, this listing is realistically open to candidates well outside Germany, not just local applicants.
Quick FAQ
Is this role open to relocation candidates? Yes — Raisin explicitly offers relocation support, so applicants moving from another city or country are welcome to apply.
Do I need prior fintech experience? It’s not explicitly required. The core bar is 5+ years of backend/platform engineering plus hands-on AI/LLM experience; domain knowledge in finance is a bonus, not a gatekeeper.
Is this a hands-on coding role or a strategy role? Both. You’re expected to build and extend real infrastructure, while also advising other teams — it’s not a purely architectural or purely IC role.
Should You Apply?
If you’re a senior backend or platform engineer who’s spent the last couple of years actually building with AI — not just reading about it — and you’d rather shape how a whole organization uses AI responsibly than ship one more isolated feature, this role is worth a serious look. The mix of technical depth, cross-team influence, and the added complexity of working in a regulated fintech environment makes it a meatier opportunity than most “AI Engineer” postings you’ll come across this year.
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