Senior DevOps & Infrastructure Engineer

Location: Remote within Brazil, with regular working-hour overlap with U.S. Pacific Time and participation in a global on-call rotation.

Company

hirify.global works with frontier AI labs and Fortune 500 enterprises to build datasets, reinforcement learning environments, research benchmarks, and end-to-end agentic AI systems.

What you will do

• Operate and continuously improve production infrastructure across GCP, AWS, and Azure, including monitoring, logging, alerting, performance, capacity, reliability, and cloud-cost efficiency.
• Lead incident response, troubleshoot complex production issues, conduct root-cause analysis, and implement durable remediation.
• Build and support developer platforms, release pipelines, deployment automation, reusable Terraform modules, and automated workflows.
• Run production Kubernetes and GKE environments across deployment, scaling, networking, security, observability, and troubleshooting.
• Design and troubleshoot cloud networking, including VPCs, firewalls, load balancers, routing, DNS, and WAFs, while partnering on identity, access, secrets, and infrastructure security.
• Mentor engineers and lead initiatives that improve reliability, security, developer productivity, debugging, log analysis, and optimization using AI-assisted engineering tools.

Requirements

• 5+ years in cloud, infrastructure, DevOps, SRE, or platform engineering, including hands-on ownership of production GCP environments.
• 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.
• Strong scripting or programming skills in Python, Go, Shell, or equivalent technologies, with experience replacing manual work with repeatable systems.
• Experience handling complex incidents, conducting root-cause analysis, communicating clearly, and implementing improvements that prevent recurrence.
• Availability for regular overlap with U.S. Pacific Time and a shared global on-call rotation is required.

Nice to have

• Independent operational experience in AWS or Azure alongside GCP.
• Experience with Ansible, Chef, Puppet, or comparable configuration-management tooling.
• Experience securing containers across Docker, Kubernetes, or GKE.
• Experience with advanced GCP controls, including Organization Policies, VPC Service Controls, Access Context Manager, and Binary Authorization.
• Google Cloud Professional certifications or comparable cloud credentials.

Culture & Benefits

• Work with a globally distributed Infrastructure Engineering team and collaborate across application and security teams.
• Build infrastructure and developer platforms supporting frontier AI research, enterprise AI deployment, and advanced model development.
• Values include client focus, startup speed, action-oriented execution, and an AI-forward approach.
• Opportunities to contribute to AI research and showcase work at conferences such as ICLR, ICML, and NeurIPS.
• Work with colleagues experienced at Google, Meta, Amazon, and other leading technology companies.