Senior Cloud Engineer - AI-ML Platform

Work Your Magic with us!

Ready to explore, break barriers, and discover more? We know you’ve got big plans – so do we! Our colleagues across the globe love innovating with science and technology to enrich people’s lives with our solutions in Healthcare, Life Science, and Electronics. Together, we dream big and are passionate about caring for our rich mix of people, customers, patients, and planet. That's why we are always looking for curious minds that see themselves imagining the unimaginable with us.

Senior Cloud Engineer – AI/ML Platform (f/m/d)

Your Role

As a Senior Cloud Engineer specialising in AI/ML Platform infrastructure, you will be at the heart of building and operating the cloud-native foundation that powers data, analytics, and artificial intelligence workloads across the organisation. In this pivotal role, you will design, deploy, and continuously improve scalable, resilient infrastructure on AWS — enabling AI/ML engineers and data scientists to develop, deploy, and monitor machine-learning models and AI services at production scale. You will own critical platform components end-to-end: from containerised workloads and streaming pipelines to networking, security, and CI/CD automation. Working at the intersection of cloud engineering, data platforms, and AI/ML operations, you will solve complex infrastructure challenges with a pragmatic, reliability-first mindset and directly shape the technical direction of a platform that drives meaningful business outcomes.

Who You Are

• You bring 5 or more years of hands-on cloud engineering experience, with strong expertise in AWS services including Elastic Container Service, Elastic Kubernetes Service, Virtual Private Cloud networking, and managed streaming solutions.

• You have proven experience provisioning and managing cloud infrastructure as code using Terraform and/or CloudFormation, and you are comfortable owning production environments end-to-end.

• You are skilled in building and maintaining CI/CD pipelines (for example using Azure DevOps) and apply disciplined version-control practices in collaborative engineering environments.

• You have hands-on experience designing and operating streaming platforms such as Apache Kafka or equivalent cloud-managed alternatives, with a focus on scalability and resilience.

• You implement platform security with confidence — including Transport Layer Security, secrets management, access controls, and authentication mechanisms such as JSON Web Tokens, OAuth, and LDAP.

• You have experience deploying, scaling, and monitoring AI/ML workloads and model-serving APIs, and you collaborate effectively with AI/ML engineers and data scientists to bring models into production.