How do you make our customers happy?
By ideating and realizing the infrastructure that turns our ambitious AI goals into AI reality. As an AI Platform Engineer, you’ll design and optimize the platforms that enable data scientists and AI users across bol to experiment, iterate, and deploy AI solutions with confidence. When teams can move from idea to production without friction, innovation accelerates. And that directly translates into smarter recommendations, faster answers, and – most importantly – better experiences for 2,900 colleagues, 46,500 partners, and 13.7 million customers.
The biggest challenge
Building AI infrastructure that’s both empowering and compliant. You’re not just spinning up cloud resources, you’re creating the foundation for how (y)our colleagues will interact with AI. How do you design self-service tooling that’s flexible enough for experimentation yet robust enough for production? How do you embed compliance and governance without slowing teams down? To maximize your impact, you’ll need to empower us to embrace emerging AI capabilities without jeopardizing enterprise-grade reliability.
What you'll do as an AI Engineer
You’ll join the newly formed AI Infra Team, positioned at the intersection of Data Infrastructure, Platform Engineering, and Data Science. Working closely with data engineers, data scientists, and platform colleagues, you’ll integrate modern Google Cloud AI tools – think Vertex AI, Agentspace, and NotebookLM – into bol’s extensive data landscape. Your ambition: to make AI experimentation frictionless, scalable, and compliant. You’ll contribute to MLOps best practices, automate pipelines, and help define the golden path that guides teams effortlessly from initial prototypes to scalable production solutions. In a team that’s still very much taking shape, you’ll have real and tangible influence over the technical direction and ways of working. Short version:
Design and develop golden paths for data scientists and AI practitioners within bol’s infrastructure
Experience with Vertex AI, Agentspace, NotebookLM, MCP servers
Build and automate data and model pipelines using Python, GCP (BigQuery, Cloud Storage), and CI/CD tooling
Contribute to MLOps standards: model deployment, monitoring, lifecycle management, and governance
Collaborate with Data Infra, Platform Engineering, and Security teams to ensure compliant AI workloads
Improve the developer experience and reliability across the AI/ML ecosystem
Participate in design reviews, RFCs, and architecture discussions
Why you can make a difference
You combine AI or ML engineering experience with a solid software engineering foundation. You’ve worked hands-on with cloud platforms (preferably GCP) before, and understand the complexity and pitfalls of building systems that others depend on. Familiarity with NotebookLM, Agentspace, or similar collaborative AI environments is obviously a plus. You have a deep understanding of MLOps principles: reproducibility, observability, continuous training, and governance, know your way around Python, and you’re comfortable with containerization and Kubernetes. Beyond the technical, you truly care about user impact, enjoy collaborating with cross-functional teams, and have a knack for explaining technical concepts lucidly.
3 reasons why this is (not) for you
Switch to find out
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Model purist
You can obsess over perfecting an algorithm for days. Ensuring users get the most out of it, is much less your cup of Darjeeling.
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Your desk is a silo
You excel as a soloist and keep a polite distance from data scientists, security experts, and platform engineers
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Certainty preferred
If something isn’t set in stone yet, you’ll wait for the ambiguity to dissipate
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Foundation fanatic
You find satisfaction in creating platforms that empower others to succeed
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Curious pragmatist
You stay current with AI developments but always ask: "How does this solve a real problem?"
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Early-stage energizer
Joining a team that's still forming, with real ownership over its direction and standards? Exciting!
Where you'll work
You’ll join the AI Infra Team. We’re a newly formed group focused on enabling safe, scalable, and efficient AI adoption across bol. The team sits at the intersection of Data Infrastructure, Platform Engineering, and Data Science, and is responsible for building foundational AI capabilities that empower teams company-wide. The environment combines technical depth with a platform mindset: reliability, developer experience, and governance matter as much as cutting-edge tooling and elegant architectures. You’ll be joining early, with genuine ownership and influence over the technical direction and long-term AI infrastructure roadmap. If you have the key to a golden path, we have a red carpet!
Perks of having a blue heart
Discover all perks
The culture and the office
Our colleagues work hard to make the daily lives of our customers easier and more fun. But of course, we do this in an inspiring and creative environment!
On and off
At bol we understand like no other that you have to take care of yourself first, then your environment and then bol. In that order. Therefore, everyone at bol receives 29 days of vacation.
Flexible working
We bring the best of both worlds together by working 50% at the office and 50% at home. This way, we find a balance between organisational and individual needs.
Interview process
We'll tell you all about applying at bol.
Your application
We’ll review your application with care. We aim to get in touch with you as soon as possible.
First contact
We’ll contact you and walk you through the process and take the first step to set up an interview. And since we’re already talking: feel free to ask any questions you may have.
First date
During the first interview we’ll get to know each other. We want to find out more about you, your work experience and skills.
Your next interview
Before this interview will take place we will ask you to take an online assessment. For some specific jobs we ask you for extra input, for example a business case or a technical assessment. We’ll also discuss the position and the team in depth.
Is this love?
Two interviews are usually enough to see if it’s a match. And if you agree… well, it’s the beautiful beginning of your career at bol.
Any questions?
I'm Monika Myslinska, Recruiter at bol. Anything I can help you with regarding the AI Platform Engineer vacancy?
Get in touch!
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