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Location - Mexico, Colombia or Argentina (remote)
Role Overview
We're looking for an experienced DevOps / Cloud Engineer to join our global DevOps team. You'll be part of a core group responsible for the reliability, scalability, and automation of our multi-cloud SaaS platform running in AWS and Azure. The environment supports hundreds of enterprise tenants and requires exceptional operational maturity, automation, and observability.
Key Responsibilities
Design, implement, and maintain CI/CD pipelines using GitOps principles (GitHub Actions, ArgoCD, etc.)
Drive automation across infrastructure provisioning, deployments, and operational workflows
Own and improve observability and monitoring , leveraging Elastic Stack or equivalent (Prometheus, Grafana, Datadog)
Develop tools and scripts (Python, Go, Bash, PowerShell) to enhance developer experience and efficiency
Manage and optimize Kubernetes infrastructure using Helm, Argo, and KEDA
Implement and maintain infrastructure-as-code across multi-cloud environments (AWS, Azure)
Participate in on-call rotations ensuring platform reliability and fast incident response
Perform root-cause analysis and postmortems for infrastructure or software failures
Collaborate closely with engineering teams to embed operational excellence and reliability into the product
Qualifications
Minimum 5 years of experience as a DevOps, SRE, or Cloud Engineer in a production SaaS environment
Strong hands-on experience with Kubernetes , Helm , and Argo
Proficient in YAML , Bash , Python , and Go
Deep understanding of CI/CD pipelines , Git , and GitOps workflows
Experience with monitoring and observability tools such as Elastic Stack, Prometheus, or Datadog
Solid understanding of AWS and/or Azure cloud services
Excellent problem-solving skills, especially in debugging distributed systems
Strong communication and collaboration skills with a DevOps mindset
Nice to Have
Experience with Terraform or Pulumi
Exposure to service mesh and secrets management solutions
Familiarity with cost optimization and performance tuning across cloud environments
