- 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
- Solid 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.
- Strong understanding of Machine Learning concepts such as data preprocessing, model evaluation, and optimization.
- Experience with Azure Machine Learning, MLflow, or Databricks for managing ML experiments and model registries.
- Ability to integrate ML workflows into CI/CD pipelines for automated deployment and governance.
Requirements
- Bachelor’s degree in a technical field, or equivalent experience
- 4+ years’ experience in an operational environment, preferred