Mid-Level DevOps Engineer

New

TruelogicCloud infrastructure

Location: LatAm; Workplace: Remote, Availability to work standard US-timezone business hours.Full-TimeMiddle

Salary not disclosed

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Job Details

Languages: Good written English and sufficient spoken English to collaborate effectively with a US-based team.
Experience: 4–6 years of experience in DevOps, cloud infrastructure, or platform engineering.
Required Skills: PythonBashKubernetesCI/CDTerraformGitHub ActionsNetworking

Have 4–6 years of experience in DevOps, cloud infrastructure, or platform engineering.
Bring strong hands-on experience with Terraform and Infrastructure as Code (IaC).
Have experience building, maintaining, and troubleshooting CI/CD pipelines; GitHub Actions is preferred.
Have experience with at least one major cloud provider; Google Cloud Platform (GCP) is strongly preferred.
Have working knowledge of Kubernetes and containerized deployment workflows.
Understand networking fundamentals, including VPCs, DNS, and firewalls.
Know Identity and Access Management (IAM), secrets management, and secure cloud authentication practices.
Have scripting experience with Python or Bash.
Be able to investigate technical issues independently, communicate blockers clearly, and document findings and solutions.
Be available to work standard US-timezone business hours.
Have good written English and sufficient spoken English to collaborate effectively with a US-based team.

Build, maintain, and improve cloud infrastructure using Terraform across multiple environments and projects.
Develop, maintain, and optimize CI/CD pipelines, primarily using GitHub Actions and OIDC-based keyless cloud authentication.
Troubleshoot infrastructure, deployment, and pipeline issues; identify root causes and implement or document solutions.
Support DevOps incidents, operational requests, and production releases.
Create and maintain technical documentation, runbooks, handoff notes, and design documents.
Review infrastructure changes proposed by other engineers and identify risks or areas for improvement.
Identify weaknesses in systems and operational processes and recommend practical, evidence-based improvements.
Collaborate with infrastructure and full-stack platform engineers on reliable, secure deployment workflows.
Use logs, tests, metrics, and other technical evidence to investigate issues and guide decisions.
Leverage AI-assisted tools for planning, code reviews, troubleshooting, and technical documentation.

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