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Total AI Systems, Inc. is looking for a serious DevOps Engineer—someone who understands infrastructure not as diagrams, but as systems that fail, recover, scale, and ship.
We run on Amazon Web Services (AWS) and are evolving from single-tenant deployments toward multi-tenant architectures. You will own how code moves from GitHub CI/CD production, how environments are secured, monitored, scaled, and how incidents are handled when things go sideways.
This is a hands-on, operator role, not a theoretical or mostly meetings position. If you enjoy building pipelines, hardening infrastructure, automating everything, and being the person engineering trusts at 3:00 AM—this role is for you.
What You'll Be Responsible For
Required Qualifications
Preferred (Strongly)
What We Mean by Nerdy
We're looking for someone who:
Job ID: 142732513
Skills:
Shell Scripting, Git, Gcp, Cloud, Docker, Terraform, Linux, Ansible, Azure, Kubernetes, Azure DevOps, AWS, monitoring and logging tools
Skills:
Continuous Integration, Continuous Deployment, security best practices in software development and deployment, AWS cloud platforms, AWS container orchestration technologies, Infrastructure as Code using Terraform, DevOps Architecture
Skills:
S3, Powershell, Route53, Prometheus, Windows, Lambda, Ec2, Terraform, Gitlab, Aws Cloud, Python, Newrelic, RDS, Bash, Devops, Jenkins, Linux, Kubernetes, SRE, Go, Opensearch, Monitoring, FSX, EKS
Skills:
Elk, Prometheus, Windows, Zabbix, Gcp, Linux, Terraform, Docker, Azure, Kubernetes, Python, AWS
Skills:
Github, Cacti, Prometheus, Kafka, Apache Tomcat, Groovy, Svn, Http Server, Shell, Terraform, Docker, Openshift, Gitlab, Python, AWS, Java, Red Hat, PowerShell, Ganglia, Ubuntu, Jenkins, Bitbucket, Ansible, Centos, Nagios, Puppet, Azure, Kubernetes, Chef, MLflow, Kubeflow, SageMaker, Hyperic, Pulsar, munin