Описание вакансии
Коротко о роли• Поддерживать production-инфраструктуру в GCP, AWS и Azure, разбирать инциденты и устранять их причины; • Развивать CI/CD и платформу разработчиков, создавать Terraform-модули и автоматизацию;
Responsibilities:
— Maintain production infrastructure across GCP, AWS, and Azure, troubleshoot incidents and resolve root causes.
— Develop CI/CD pipelines and developer platforms, create Terraform modules and automation.
— Operate Kubernetes and GKE environments including scaling, networking, security, and observability.
— Participate in a global on-call rotation.
— Lead incident response, improve monitoring, logging, alerting, performance, capacity, and cloud cost efficiency.
— Build and support engineering platforms, release pipelines, and deployment automation using GitHub Actions, Google Cloud Build, Jenkins.
— Design and troubleshoot cloud networking including VPCs, firewalls, load balancers, routing, DNS, and WAFs.
— Collaborate with security and engineering teams on identity and access management, secrets management, network security, and infrastructure security controls.
— Use AI-assisted engineering tools to enhance log analysis, debugging, troubleshooting, and optimization.
— Mentor engineers and lead initiatives to improve reliability, security, and developer productivity.
Requirements:
— 5+ years experience in cloud, infrastructure, DevOps, SRE, or platform engineering with hands-on production GCP experience.
— Independent experience with Terraform, CI/CD systems such as GitHub Actions, Jenkins, Cloud Deploy, or equivalents, and production Kubernetes.
— Strong knowledge of cloud architecture, distributed systems, VPCs, firewalls, load balancers, WAFs, and securing cloud environments.
— Proficient in programming or scripting with Python, Go, Shell, or similar technologies.
— Experience handling complex incidents, root-cause analysis, and implementing durable remediation.
— Operational experience in AWS or Azure alongside GCP is a plus.
— Experience with configuration management tools like Ansible, Chef, or Puppet is advantageous.
— Experience securing containers across Docker, Kubernetes, or GKE.
— Familiarity with advanced GCP controls such as Organization Policies, VPC Service Controls, Access Context Manager, and Binary Authorization.
— Google Cloud Professional certifications or comparable cloud credentials are a plus.
Benefits:
— Work remotely from Brazil or Colombia with regular overlap with U.S. Pacific Time.
— Join a global infrastructure engineering team supporting frontier AI labs and enterprise deployments.
— Opportunity to contribute to cutting-edge AI research and enterprise AI systems.
— Collaborate with experienced colleagues from leading technology companies.
— Participate in a shared global on-call rotation.
— Equal opportunity employer committed to diversity and inclusion.
— Encouragement to apply even if not all qualifications are met exactly.
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