AI Enablement Engineer

Posted 11 Days Ago
Be an Early Applicant
Nijmegen, NLD
Hybrid
Senior level
Artificial Intelligence • Healthtech
The Role
Lead AI enablement by identifying workflows for automation, building production-grade LLM and AI tools, driving internal adoption, and operating the supporting AWS, GitOps, CI/CD, and Kubernetes platform. Own solutions end to end from stakeholder discovery through deployment, observability, scaling, cost management, and production support.
Summary Generated by Built In

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? Please apply using the application button.

Providing a Certificate of Conduct (VOG) or background check is part of our application procedure. Questions about the contents of the vacancy or the recruitment process at ScreenPoint Medical? Please send an email to [email protected]. Please note that applications submitted via this email address will not be reviewed. To apply, please use the ‘Apply for this job’ button.

Skills Required

  • Experience building with AI or LLM tooling, including APIs, agents, orchestration frameworks, or automation; alternatively, strong software engineering skills with demonstrated momentum toward AI tooling.
  • At least 7 years of DevOps experience supporting cloud development.
  • The last 1–2 years focused on AI enablement and tooling.
  • Strong hands-on experience with AWS, Argo, Jenkins, Git, Terraform, CI/CD pipeline design, and Infrastructure as Code.
  • Practical Kubernetes experience involving deployment, scaling, troubleshooting, and cluster operations.
  • Knowledge of Bitbucket.
  • Experience in regulated or healthcare software environments.
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The Company
HQ: Nijmegen
66 Employees
Year Founded: 2014

What We Do

ScreenPoint helps radiologists detect breast cancer confidently and faster. We develop and market image analysis and machine learning applications and services to improve early detection of breast cancer. Our flagship product - Transpara - has been evaluated in over 35+ peer-reviewed publications and has demonstrated consistent results, regardless of patient age, breast density, or ethnicity. Transpara uses the latest developments in machine learning such as Deep Learning and is trained with very large well curated databases of screening mammograms. Research and development at ScreenPoint is aimed at improving performance to the level of expert radiologists and beyond.

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