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.