Senior Data Engineer, Cloud & Analytics
ADEAL Systems GmbH
Build cloud, data, and analytics solutions for ADEAL Systems, taking technical ownership of architecture, data pipelines, and customer projects.
Open
ScreenPoint Medical is a healthcare technology company focused on AI-assisted breast imaging. Its Transpara software suite supports mammography and clinical review through automated cancer detection, breast density assessment, and comparison of images over time. Delivered as subscription software within existing clinical workflows, Transpara is designed to help radiologists assess breast images, identify potentially high-risk cases, and work more efficiently, including when reviewing dense breast tissue. The company’s approach is grounded in clinical evidence, peer-reviewed validation, and regulatory clearances including FDA clearance and CE marking.
Senior AI Enablement Engineer – Nijmegen Hybrid
Lead the development and adoption of production-grade AI tools and automation for ScreenPoint Medical’s breast cancer imaging products. Own AWS, Kubernetes, GitOps-based CI/CD, and internal AI enablement.
Description
- Lead ScreenPoint Medical’s AI enablement strategy
- Assess internal workflows for automation and decide which initiatives to prioritize
- Develop AI-powered tools that improve internal workflows in partnership with the teams responsible for them
- Embed security considerations across solution design and implementation
- Promote internal AI adoption and help colleagues and teams realize value from new tooling
- Deliver production-ready internal tools rapidly, evolving proofs of concept into solutions used every day
- Incorporate LLM and AI capabilities—including APIs, agents, retrieval-augmented generation, and automation frameworks—into tools and pipelines
- Create and operate GitOps-driven CI/CD pipelines
- Manage and enhance Kubernetes infrastructure, covering deployments, scaling, observability, and cost control
- Own solutions throughout their lifecycle, from initial concept to production support
Requirements
- Proactive self-starter who can manage AI enablement from stakeholder discussions through delivery, operations, and adoption
- Demonstrated ability to create new solutions and lead organizational change
- Experience developing with AI and LLM tools such as APIs, agent or orchestration frameworks, and automation systems; alternatively, strong software engineering experience with clear progress toward AI tooling
- At least seven years of DevOps experience supporting cloud-based development
- One to two years of recent focus on AI enablement and tooling
- Advanced practical DevOps experience with AWS, Argo, Jenkins, Git, Terraform, CI/CD architecture, and infrastructure as code
- Practical Kubernetes expertise spanning deployment, scaling, troubleshooting, and cluster operations
- Bitbucket experience is preferred
- Experience in regulated or healthcare software environments is preferred
- A Certificate of Conduct (VOG) or background check is required during the application process
Benefits
- Opportunities to develop your career
- The application process includes a Certificate of Conduct (VOG) or background check
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