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Production Engineer (DevOps)


Soluto has been a DevOps shop way before it became what all the cool kids do, and we have a lot of history and experience with CI/CD. We’re facing some exciting opportunities and challenges, with a production deployment serving tens of millions of users, through some of the most demanding and SLA-aware customers, like Verizon, AT&T and Walmart.

We’re looking for engineers who can lead us to the next level: manage and improve our CI/CD and monitoring, but also have great coding skills so that they’re able to contribute to production code. So if you’re a developer who’s really into DevOps, and you have lots of experience with CI/CD as well as monitoring large production deployments, you could be a great fit.

As part of our DevOps team you will:

  • Promote DevOps culture and empower R&D teams through self-service tools
  • Develop and maintain high scale Kubernetes clusters
  • Design, build and maintain our CI/CD process from check-in to production
  • Automate and streamline our gradual deployment process for mobile apps, backend services and websites
  • Build tools that will help teams easily monitor their products at scale and ensure the health and reliability of our platform
  • Develop SDKs and deploy code into our apps and services that will help provide visibility, advanced monitoring, metrics and logging.
  • Implement and integrate security best practices

Here are some more details on the type of experience we’re looking for:

  • Any mainstream programing language, along with popular scripting languages
  • Continuous integration tools like Jenkins, TeamCity, Travis or similar
  • Continuous delivery methodologies for backend services and mobile apps
  • Experience working on a public cloud such as AWS, GCP or Azure
  • Defining network topologies and security considerations
  • Monitoring tools, like Nagios, Sensu, Icinga or similar
  • Configuration management tools like Puppet, Chef, Ansible or similar
  • Creating highly scalable docker deployments
  • Orchestrating container workloads using Kubernetes, Swarm or similar


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