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

• Bachelor’s degree in a technical field, or equivalent experience
  
  


• 4+ years’ experience in an operational environment, preferred
  
  

• 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.