AI Governance Engineer (Hybrid)

At Deeploy, we help organizations roll out AI they can trust. As an AI Governance Engineer, you'll own the technical implementation of our AI governance platform across customer environments, from first proof-of-concept to full adoption. No two environments are the same, and neither are the solutions you'll build.

This is an engineering role for someone who goes deep on implementation and understands that AI governance only works when it's built into the system, not bolted on afterward. You'll translate regulatory and compliance requirements into concrete technical configurations on the Deeploy platform, and make sure what gets built actually holds up in production. You'll report directly to the COO and work closely with sales and product, giving you direct influence over both customer outcomes and how the product evolves. This role is hybrid, based in Utrecht.

Why Deeploy?

AI is being rolled out everywhere, but most of it is a black box. Deeploy exists to change that. We build the technical foundation that makes AI truly responsible: helping companies detect, understand, and prevent the harms caused by misaligned AI systems before they impact the real world.

We're an AI-native team. That means we don't just build for AI, we aim to be a frontrunner in our own work. We're constantly rethinking how we operate, and we expect everyone on the team to be part of that evolution.

What you will do

• Design and deliver proof-of-concepts that demonstrate how governance requirements translate into measurable, working configurations within a customer's existing AI infrastructure

• Own technical implementation end-to-end: from mapping compliance requirements to scoping, integration, and go-live

• Build trusted relationships with technical and non-technical stakeholders across customer accounts

• Identify expansion opportunities and flag them to the sales team with clear context

• Translate customer feedback and implementation patterns into product insights

• Build reusable playbooks, templates, and integration guides that scale the team's capacity

Who we are looking for

Most engineers treat compliance as someone else's problem. You see it as an engineering challenge. You know your way around ML pipelines, understand what governance requirements actually demand at the infrastructure level, and can make both a data scientist and a legal team trust your work.

Must-Haves

• 2-5 years in a technical implementation, solution engineering, or ML engineering role

• Hands-on experience with data, AI, or ML workflows in a production context, and an understanding of what governance and compliance mean at that layer

• Comfort working across technical stakeholders (data scientists, ML engineers, IT) and business stakeholders simultaneously

• Fluency in English and Dutch

• A degree in a technical field (Engineering, Data Science, Econometrics, or similar)

Nice-to-Haves

• Experience in regulated industries (finance, healthcare, public sector)

• Familiarity with AI compliance frameworks (EU AI Act, model risk management)

• Experience in a start-up or fast-paced scale-up environment

What to expect from us

Shape the Future of AI: Work at the forefront of AI governance, transparency, and compliance, helping organizations innovate responsibly and create meaningful impact.

Collaborative Culture: Be part of a team that values openness, inclusivity, and collaboration. At Deeploy, every voice matters, and diverse perspectives drive our innovation.

Growth Opportunities: Access opportunities to learn, develop, and advance your career in a fast-growing company dedicated to transforming the AI landscape.

Competitive Benefits: Enjoy a competitive salary, stock options, and a comprehensive benefits package, including a pension plan.

Flexibility and Balance: Thrive in a flexible, hybrid work environment that supports your personal and professional well-being.

Our Hiring Process

We value efficiency and transparency. Here’s what to expect:

1. Application: Share your LinkedIn/CV and any personal projects you're proud of.

2. Introductory Call: A 20-minute chat to introduce our team and learn more about you.

3. Personal & Team Fit: A 60-minute chat with 2 team members you would work with in the future

4. Case Study: Prepare a case (timeboxed to 3 hours) and present it in a follow-up meeting with two team members.

5. Offer: If we’re a fit, we’ll extend an offer and welcome you aboard!

Got questions? Reach out anytime at [email protected].