DevOps Engineer 

Who we are, what we are doing? 

• Language Cloud is a SaaS platform developed by SDL that exposes as a service the best of our language capabilities and of the language expertise that made us leaders in the translation industry. 

 

• We are building Language Cloud in a microservice architecture using Java and C#. Our engineers are familiar with multiple build and deploy pipelines. We implement Continuous Delivery by using tools like Chef, Jenkins, Spinnaker, Kubernetes, Nexus and deploying our services in AWS. 

 

What you’ll be doing: 

• Build and operate the only end-to-end intelligent translation management solution;
• Work closely with the Core Components and product teams throughout the dev lifecycle and deployment process, to ensure high-quality releases and successful outcomes;
• Responsible for application deployments, monitoring, and overall service availability;
• Understand system limitations and building observability tools to maintain infrastructure              reliability and/or alert on potential production issues;
• Configuration and management of: Windows-based service node VMs/EC2 instances, Kubernetes clusters, Docker containers, .NET Framework and .NET Core services, MongoDB clusters, MS SQL and AWS Aurora PostgreSql clusters, RabbitMQ, Redis and related technologies;
• Release management using Azure DevOps, Spinnaker, Chef, Jenkins, Kubernetes, Nexus.

 

What we’re looking for: 

• Strong team player with excellent communication, documentation and problem-solving skills;
• Experience with Windows system administration including managing servers, scripting, networking, performance tuning, troubleshooting and internals;
• 3+ years of relevant experience in similar roles 
• Capable to independently investigate, and solve complex software issues with minimal supervision;
• Familiarity with Kubernetes, Docker and AWS represents a major advantage;

 

 

What makes you a great fit: 

• Strong Windows administration knowledge;
• Experience with Cloud platforms and AWS;
• Experience with Chef/Jenkins/Spinnaker/Kubernetes or other similar technologies;
• Experience working with large-scale workflows and distributed processing systems.

 

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