Customer Engineer, AI Governance

# Customer Engineer, AI Governance

At Deeploy, help organizations deploy AI they can trust. As a Customer Engineer, you'll own the technical journey from first proof-of-concept to full platform adoption, turning complex customer environments into working, compliant AI governance setups.

This is a hands-on role for someone equally comfortable in customer conversations and deep technical implementation. You'll engage stakeholders across data science, engineering, legal, and compliance, translating their needs into concrete implementations on the Deeploy platform. You'll report directly to the COO and work closely with sales and product, giving you direct influence over both customer outcomes and product evolution.

## What you will do

• Design and deliver proof-of-concepts that demonstrate measurable value within a customer's existing AI infrastructure
• Own onboarding and implementation end-to-end, from scoping through 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

This role sits at an unusual intersection: deep enough to debug an MLflow integration, sharp enough to explain model risk to a CFO.

### Must-Haves

• 2-5 years in a solution engineering, implementation, or technical customer success role
• Hands-on experience with data, AI, or ML workflows in a production context
• 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 (e.g., finance, healthcare, public sector)
• Familiarity with AI compliance frameworks (e.g., EU AI Act, model risk management)
• Experience in a start-up or fast-paced scale-up environment