Senior DevOps Engineer – AI & Data Platform

We are Systematix and we are currently looking for a Senior Dev Ops Engineer - AI & Data Platform to help modernize and automate the engineering practices supporting a rapidly growing enterprise AI and Data ecosystem for one of our key clients.

Our client is a global leader in science and technology, supporting a diverse portfolio of businesses across healthcare, life sciences, diagnostics, manufacturing and industrial innovation. As investment in AI, machine learning and advanced data capabilities continues to accelerate, the organization is modernizing the engineering practices and automation required to support these workloads at enterprise scale.

The primary objective is to eliminate manual infrastructure, build and deployment processes and replace them with automated, repeatable and reliable engineering pipelines. Working closely with Platform Engineering, MLOps and other technical teams, the successful candidate will help establish modern Dev Ops patterns and standards while remaining highly hands-on in their implementation.

• Design, build and maintain CI/CD pipelines supporting cloud infrastructure, applications and AI/ML workloads.
• Provide hands‑on operational support for Dev Ops/platform services, working within established ticketing, incident management and escalation processes to troubleshoot and resolve infrastructure, pipeline and deployment issues.
• Implement Infrastructure as Code and automated Azure cloud provisioning.
• Create standardized and repeatable Development, UAT and Production deployment patterns.
• Automate application and infrastructure testing, validation, deployment and release processes.
• Develop reusable engineering tooling, templates and automation components.
• Integrate infrastructure and deployment automation with Git Hub‑based development workflows.
• Design and implement Git Hub Actions or equivalent CI/CD workflows.
• Support containerized applications and workloads using Docker and Kubernetes.
• Partner with Platform Engineering teams to automate Azure infrastructure provisioning and deployment.
• Partner with MLOps engineers to automate machine learning lifecycle, deployment and operational processes.
• Build self‑service capabilities that enable development, data science and machine learning teams to deploy and consume technology with minimal manual intervention.
• Identify manual engineering processes and replace them with scalable, code‑driven automation.
• Improve deployment speed, consistency, repeatability, reliability and overall developer experience.
• Implement appropriate security, governance and operational controls within automated engineering processes.
• Help establish modern SDLC, Dev Ops, source control, deployment and engineering standards.
• Provide technical leadership and recommendations while remaining directly involved in engineering, coding, configuration and implementation.

• Extensive senior‑level (10+ years) Dev Ops engineering experience within complex enterprise environments.
• Strong hands‑on experience with Microsoft Azure.
• Experience operating within enterprise support models, including ticket queues, incident management, troubleshooting, escalation procedures and coordination across technical support teams.
• Demonstrated expertise with Infrastructure as Code and automated cloud provisioning.
• Strong experience designing, building and maintaining enterprise CI/CD pipelines.
• Hands‑on experience with Git Hub, Git Hub Actions or comparable Git‑based CI/CD technologies.
• Strong experience with Docker, Kubernetes and containerized workloads.
• Advanced scripting and automation capabilities.
• Strong understanding of modern SDLC, source control, release management and deployment practices.
• Experience developing reusable…