Senior DevOps & Infrastructure Engineer

BrazilRemoteFull-timesenior

EngineeringDevops Engineer

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Quick Summary

Key Responsibilities

Operate and continuously improve production infrastructure across Google Cloud Platform (GCP), AWS, and Azure, with a strong focus on GCP. Lead incident response,

Requirements Summary

At least 5 years of experience in cloud engineering, infrastructure, DevOps, Site Reliability Engineering (SRE), or platform engineering.

Technical Tools

EngineeringDevops Engineer

Join a global Infrastructure Engineering team responsible for building and maintaining the cloud infrastructure and developer platforms that support business-critical operations. In this hands-on role, you will strengthen the reliability, security, scalability, and efficiency of production systems across multiple cloud environments. You will take ownership of infrastructure automation, Kubernetes operations, CI/CD pipelines, and cloud networking while resolving complex production challenges. Working closely with application and security teams, you will help establish robust engineering practices and improve developer productivity. The position offers broad technical ownership and the opportunity to contribute to systems supporting advanced AI research and enterprise AI solutions. This is a remote opportunity within Brazil, with regular collaboration during U.S. Pacific Time working hours and participation in a shared global on-call rotation.

As a Senior DevOps & Infrastructure Engineer, you will own critical infrastructure initiatives, improve operational standards, and help engineering teams deliver software reliably and securely. Your responsibilities will include:

Operate and continuously improve production infrastructure across Google Cloud Platform (GCP), AWS, and Azure, with a strong focus on GCP.
Lead incident response, troubleshoot complex production issues, conduct root-cause analyses, and implement lasting solutions to prevent recurrence.
Improve infrastructure monitoring, logging, alerting, performance, capacity planning, and cloud-cost efficiency.
Build and maintain developer platforms, release pipelines, and deployment automation using GitHub Actions, Google Cloud Build, Jenkins, and related tools.
Develop reusable Terraform modules and automate infrastructure workflows using Python, Go, Shell, or comparable programming and scripting languages.
Operate production Kubernetes and GKE environments, covering deployment, scaling, networking, security, observability, and troubleshooting.
Design and maintain secure cloud networking components, including VPCs, firewalls, load balancers, routing, DNS, and Web Application Firewalls (WAFs).
Collaborate with security and engineering teams on identity and access management, secrets management, network security, and infrastructure protection.
Use AI-assisted engineering tools to improve log analysis, debugging, troubleshooting, and infrastructure optimization.
Contribute to scalable architecture and production best practices, mentor other engineers, and lead initiatives that strengthen reliability, security, and developer productivity.
Participate in a shared global on-call rotation, responding to production incidents and following through on remediation.
Collaborate regularly with colleagues working in U.S. Pacific Time and communicate effectively across distributed teams.

Requirements

~2 min read

The ideal candidate is an experienced infrastructure or platform engineer with strong production cloud expertise, practical automation skills, and a proven ability to take ownership of complex operational challenges. You should bring:

At least 5 years of experience in cloud engineering, infrastructure, DevOps, Site Reliability Engineering (SRE), or platform engineering.
Hands-on experience owning and operating production environments on Google Cloud Platform (GCP).
Independent experience with Infrastructure as Code (IaC), particularly Terraform, including the development and maintenance of reusable modules.
Practical knowledge of CI/CD systems such as GitHub Actions, Jenkins, Google Cloud Build, Cloud Deploy, or equivalent tools.
Production experience with Kubernetes, particularly GKE, including deployment, scaling, networking, security, observability, and troubleshooting.
Strong understanding of cloud architecture, distributed systems, and infrastructure networking, including VPCs, firewalls, load balancers, routing, DNS, and WAFs.
Strong scripting or programming capabilities in Python, Go, Shell, or equivalent technologies, with an ability to replace manual processes through reliable automation.
Experience managing complex production incidents, performing root-cause analysis, communicating clearly, and implementing improvements that reduce future operational risks.
Willingness to participate in a shared global on-call rotation and respond to infrastructure incidents during scheduled periods.
Ability to collaborate effectively with a globally distributed team, including regular working-hour overlap with U.S. Pacific Time.

Additional experience that would be advantageous includes:

Independent operational experience with AWS or Azure alongside GCP.
Familiarity with configuration-management tools such as Ansible, Chef, or Puppet.
Experience securing containers and containerized environments using Docker, Kubernetes, or GKE.
Knowledge of advanced GCP security and governance controls, including Organization Policies, VPC Service Controls, Access Context Manager, and Binary Authorization.
Google Cloud Professional certifications or comparable cloud credentials.

What We Offer

~2 min read

✓Opportunity to work on the frontier of AI, supporting the development of expert datasets, reinforcement learning environments, and advanced benchmarks for leading AI labs.

✓Exposure to cutting-edge AI research, with opportunities to showcase work at leading conferences such as ICLR, ICML, and NeurIPS.

✓The chance to apply frontier AI innovations to real-world enterprise challenges and business-critical workflows.

✓Collaboration and knowledge-sharing with experienced professionals from leading technology companies, including Google, Meta, and Amazon.

✓A fast-paced, startup-oriented environment offering meaningful ownership, technical challenges, and opportunities to make a direct impact.

✓The opportunity to contribute to a global infrastructure platform supporting advanced AI research and enterprise AI applications.

✓Remote work arrangement for candidates based in Brazil, with regular overlap with U.S. Pacific Time working hours.