AI Enablement Engineer

ScreenPoint Medical BV; Nijmegen; Hybrid; EUR 85,000 - 120,000; Full time

Job summary

ScreenPoint Medical BV is seeking a DevOps engineer to lead AI enablement, design and ship automation and AI-powered tools, and own the cloud foundation including CI/CD pipelines and Kubernetes deployments. You will drive adoption across teams and ensure production-grade quality.

The ideal candidate has 7+ years in DevOps for cloud development, strong AI tooling momentum, and hands-on experience with AWS, Argo, Jenkins, Terraform, and Kubernetes.

Qualifications

• Experience building AI/LLM tooling or strong software engineering momentum toward AI tooling.
• 7+ years in DevOps supporting cloud development, with 1–2 years focused on AI enablement.
• Hands-on DevOps expertise: AWS, Argo, Jenkins, Git, Terraform, CI/CD pipelines, IaC.
• Solid knowledge of Kubernetes: deployments, scaling, troubleshooting, observability.

Responsibilities

• Lead AI enablement by identifying workflows to automate and building AI-powered tools.
• Drive adoption by evangelizing AI tooling and helping teams extract value.
• Be hands-on by shipping production-grade internal tools from POC to daily use.
• Integrate AI capabilities (APIs, agents, automation) into internal tools and pipelines.
• Own the platform: design and maintain GitOps CI/CD pipelines and Kubernetes infrastructure.
• Take full ownership from idea to production support.

Skills

AI tooling experience

DevOps leadership

Cloud infrastructure

Kubernetes

Tools

AWS

Argo

Jenkins

Git

Terraform

CI/CD

Job description

In the fight against breast cancer, every medical image is an opportunity: to unlock insight, to uncover risk, to embody health, to empower life. ScreenPoint’s Transpara Breast AI delivers unmatched precision for breast radiologists and helps define personalized care pathways for every woman we serve. Make your mark as part of The Breast AI Company.

This is a hybrid role with a clear primary objective: lead ScreenPoint Medical's AI enablement effort, designing and shipping automation and AI-powered tools that help the company move faster and safer, and driving adoption of those tools across teams. To do this at production quality and pace, you'll also own the cloud foundation underneath it - infrastructure, CI/CD pipelines, and Kubernetes - as an experienced DevOps engineer. The DevOps half isn't a separate job; it's what lets you take AI tooling from idea to something colleagues rely on daily, safely and reliably.

Responsibilities:

• Lead AI enablement: identify internal workflows worth automating, prioritize what gets built, and build AI-powered tools to speed them up - in collaboration with the teams that own those workflows, with security as a guiding principle throughout design and build.
• Drive adoption: evangelize AI tooling internally and help colleagues and teams get value from what you build, not just ship it.
• Be hands-on: build internal production-grade tools - ship fast, iterate, and take things from POC to something colleagues work with and rely on daily.
• Integrate LLM/AI capabilities (APIs, agents, RAG, automation frameworks) into internal tools and pipelines.
• Own the platform that makes this possible: design, build, and maintain GitOps-based CI/CD pipelines, and own and evolve our Kubernetes-based infrastructure (deployments, scaling, observability, cost).
• Take full ownership of what you build - from idea to production support.

Job requirements

You are a self-starter who can lead AI enablement end-to-end: from talking to a stakeholder about a painful process, to shipping, operating, and driving adoption of the tool that fixes it. You have a track record of inventing solutions and driving change, not just executing tickets.Moreover, you have:

• Experience building with AI/LLM tooling (APIs, agent/orchestration frameworks, automation) - or strong software engineering skills with clear, demonstrated momentum toward AI tooling.
• At least 7 years of experience in DevOps supporting cloud development, with the last 1-2 years focused on AI enablement and tooling - this depth is what lets you ship AI tools that are actually production-grade, not just prototypes.
• Strong hands-on DevOps experience: AWS, Argo, Jenkins, Git, Terraform, CI/CD pipeline design, Infrastructure-as-Code.
• Solid, practical knowledge of Kubernetes - deployment, scaling, troubleshooting, cluster operations.

Preferred qualifications:

• Knowledge in BitBucket.
• Background in regulated or healthcare software environments.

About us

ScreenPoint Medical is a leading company that develops and markets breast image analysis and cutting edge machine learning applications and services. Our product Transpara improves breast cancer survival rates by detecting cancers earlier so that treatment can be more effective and less invasive.

Do you want to help us build an innovative solution to improve health worldwide? And do you want to be part of an ambitious and fast-growing team who help you develop your career further?