3 hours ago
Remote, BrazilSenior
Responsibilities
- Operate and continuously improve production infrastructure across GCP, AWS, and Azure.
- Lead incident response, troubleshoot complex production issues, perform root-cause analysis, and implement durable remediation.
- Improve monitoring, logging, alerting, performance, capacity, reliability, and cloud-cost efficiency.
- Build and support engineering platforms, release pipelines, and deployment automation.
- Develop reusable Terraform modules and automate workflows with Python, Go, Shell, or similar technologies.
- Run production Kubernetes and GKE environments, including deployment, scaling, networking, security, observability, and troubleshooting.
- Design and troubleshoot cloud networking involving VPCs, firewalls, load balancers, routing, DNS, and WAFs.
- Partner with security and engineering teams on identity and access management, secrets management, network security, and infrastructure-security controls.
- Mentor engineers and lead initiatives that improve reliability, security, and developer productivity.
- Participate in a shared global on-call rotation and respond to production incidents.
Requirements
- At least 5 years of experience in cloud, infrastructure, DevOps, SRE, or platform engineering.
- Hands-on ownership of production GCP environments.
- Independent experience with Terraform, CI/CD systems such as GitHub Actions or Jenkins, and production Kubernetes.
- Strong knowledge of cloud architecture, distributed systems, VPCs, firewalls, load balancers, WAFs, and securing cloud environments.
- Strong scripting or programming skills in Python, Go, Shell, or equivalent technologies.
- Experience handling complex incidents, conducting root-cause analysis, communicating clearly, and implementing preventive improvements.
- Preferred experience operating AWS or Azure alongside GCP.
- Preferred experience with Ansible, Chef, or Puppet.
- Preferred experience securing containers across Docker, Kubernetes, or GKE.
- Preferred experience with GCP Organization Policies, VPC Service Controls, Access Context Manager, and Binary Authorization.
- Google Cloud Professional certifications or comparable cloud credentials are preferred.
Benefits
- Remote work within Brazil.
- Regular working-hour overlap with U.S. Pacific Time.
- Participation in a global shared on-call rotation.
- Opportunity to work on infrastructure supporting frontier AI labs and enterprise AI deployments.
- Opportunities to contribute to AI research and collaborate with experienced colleagues from major technology companies.
Tech Stack
AnsibleAWSAzureChefDockerGitHub ActionsGoGoogle Cloud PlatformJenkinsKubernetesPuppetPythonTerraform
Categories
DevOpsSite Reliability
About Turing
Turing builds AI data pipelines and systems for enterprises and AI labs. It creates large-scale datasets and reinforcement-learning environments to train and evaluate models, and deploys agentic AI applications in domains like software engineering and enterprise workflows. The company also operates an AI-powered talent cloud to match and manage developers and AI trainers. Founded in 2018 and headquartered in San Francisco, it is privately held and serves Fortune 500 customers.