• Experience and deep understanding working within a DevOps environment.
• Solid technical background/understanding in DevOps, Software Engineering or Infrastructure Engineering so that you're able to understand high level technical briefs, talks and ideas.
• Experience with various monitoring solutions namely Dynatrace, App Dynamics, Grafana etc.
• Experience of the full software delivery lifecycle and working in complex enterprise environments.
• Experience with Windows systems engineering and Linux as well.
• Strong experience in multiple public clouds.
• Experienced in CI/CD Pipelines with GitHub Actions
• Strong grasp of container technology including container orchestration with tools such as Kubernetes, Rancher, Docker Swarm, Nomad or similar.
• Solid understanding of Microservices and APIs.
• Experience/ Interest working in an Agile environment.
• Oversight of critical incident and major system escalations from initiation to resolution
• Create mechanisms/architectures that enable fault tolerance and rapid recovery from failure
• Strong communication skills, verbal and written
• Create and maintain configuration standards for software and infrastructure
• Strong proficiency in Python scripting for automation and integration tasks.
• Proven experience in designing and developing CI/CD pipelines from scratch using YAML scripting within Azure DevOps.
• Hands-on experience managing branching strategies, resolving merge conflicts, and maintaining projects and repositories as an Azure DevOps administrator.
• Familiarity with infrastructure automation and integration of deployment workflows across multiple environments.
• Practical experience implementing MLOps pipelines for end-to-end machine learning lifecycle management - including model training, versioning, deployment, and monitoring.
• Robust understanding of Machine Learning concepts such as data preprocessing, model evaluation, and optimization.