AWS Cloud DevOps Engineer

Overview

In this role you will architect, deploy and support AI-enabled solutions at scale, with a focus on GenAI projects. You will contribute to the platform’s capabilities and drive production ML workflows. You’ll work closely with cross-functional teams to deliver reliable, auditable ML systems and automated pipelines. This position sits inside the AI Enablement Team and offers a hybrid work model in London, enabling collaboration while supporting continuous learning and innovation. You will shape the AI platform to empower the organization and its clients.

Pay / Benefits

• Hybrid work model
• collaborative and inclusive environment
• opportunity to shape AI platform
• global/multicultural team
• focus on learning and career development

Responsibilities

• Design machine learning deployment and monitoring pipelines and the supporting infrastructure.
• Operationalize offline models into production ML systems.
• Build and deploy scalable tools for ML training and inference.
• Evaluate new technologies to improve performance, maintainability, and reliability of ML systems.
• Apply software engineering best practices to ML, including CI/CD and automation.
• Support model development with emphasis on auditability, versioning, and data security.
• Facilitate development and deployment of proof-of-concept ML systems.
• Engage with clients to gather requirements and track progress.

Key requirements

• 5–8 years in cloud application development/administration with at least 4 years on AWS and Terraform, Jenkins, CloudFormation or equivalent IaC.
• Proven experience building end-to-end platform engineering/ML DevOps on AWS Sagemaker or similar tools.
• Hands-on skills in automation (Jenkins, GitLab, Docker, Kubernetes, Shell scripting).
• Experience in automation, infrastructure as code, logging/monitoring, and security-conscious scripting.
• Cloud experience deploying workloads, preferably on AWS.
• Associate AWS Development/Architect certification or related cloud certs preferred.
• Understanding of AI/ML and Generative AI domains is advantageous.
• Strong communication, prioritization skills, and ability to work with remote/multicultural teams.
• Knowledge of Chef, Python, Go, and cloud networking; essential security practices.

• excellent communication
• collaborative and supportive
• analytical and well-organized
• AWS
• Terraform
• Jenkins

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