DevOps Engineer

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. 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

Qualifications Bachelor’s degree in a technical field, or equivalent experience 4+ years’ experience in an operational environment, preferred Technical

Requirements Experience with Linux, Windows and Mac platforms Experience in network and server engineering Experience with automation/configuration management such as Ansible, Chef, Puppet or equivalent Strong competency with cloud providers such as Azure. Demonstrated experience installing, operating and troubleshooting a variety of open source technologies Experience with relational and non-relational databases Practical experience developing software or meeting operational needs with code and scripting (Bash, Python, Perl, Ruby, or Java) Experience with software quality principles and associated tools for testing and analysis. Knowledge of CI & CD practices and supporting tools (Jenkins, Bamboo or similar) Experience with Pipelines, YAML, Helm Demonstrated experience in documenting, designing and re-designing process in an enterprise environment Experience with PaaS technologies such as containers, container orchestration and scheduling, service registration / discovery and monitoring (Docker, Kubernetes, etc.) Experience with automation in dynamic environments such as IaaS and PaaS Experience with OpenText Archive and ICC Server will be an advantage. Experience with Akamai CDN or similar is preferred.