Want to know if this job is worth applying to?
Brasil
Remote only
Turing’s mission is to accelerate superintelligence to drive real economic progress. Headquartered in San Francisco, Turing works with frontier AI labs to generate high-quality datasets, reinforcement learning environments, and frontier research benchmarks that improve model capabilities in software engineering, enterprise knowledge work, and advanced STEM reasoning. In software engineering, Turing is the largest and longest-running data provider in the category. Turing also works with Fortune 500 enterprises across financial services, life sciences, healthcare, retail, automotive, and CPG to build and deploy end-to-end agentic AI systems inside mission-critical workflows. By operating on both sides, Turing closes the loop between frontier research and enterprise deployment, turning real-world deployment signals into better data, evaluations, and more capable models. Learn more at www.turing.com.
Role: Senior DevOps & Infrastructure Engineer
Location: Brazil
Experience Level: 5+ years in cloud, infrastructure, DevOps, SRE, or platform engineering
Work Model: Remote within Brazil, with regular working-hour overlap with U.S. Pacific Time and participation in a global on-call rotation
Join Turing's global Infrastructure Engineering team and help build the cloud infrastructure and developer platform that power our business. You will make the systems engineers rely on more reliable, secure, scalable, and efficient as the company grows.
This is a hands-on role for an engineer who enjoys turning manual work into durable automation, solving difficult production problems, and raising the bar for operational excellence. You will work across cloud infrastructure, reliability, developer tooling, and security in close partnership with application and security teams.
You will have meaningful ownership in a globally distributed team: working regularly with colleagues in U.S. Pacific Time, participating in the shared on-call rotation, and building systems that allow engineers to ship faster with confidence.
Operate and continuously improve production infrastructure across GCP, AWS, and Azure. Lead incident response, troubleshoot complex issues, drive root-cause remediation, and 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, and related tooling. Develop reusable Terraform modules and automate workflows with Python, Go, Shell, or similar technologies.
Run production Kubernetes and GKE environments across deployment, scaling, networking, security, observability, and troubleshooting. Build infrastructure that is secure and scalable without making engineering teams slower.
Design and troubleshoot cloud networking, including VPCs, firewalls, load balancers, routing, DNS, and WAFs. Partner with security and engineering teams on identity and access management, secrets management, network security, and broader infrastructure-security controls.
Use AI-assisted engineering tools to improve log analysis, debugging, troubleshooting, and optimization. Collaborate on scalable architectures and production best practices, mentor engineers, and lead initiatives that improve reliability, security, and developer productivity.
On-call is part of the job: You will participate in a shared global on-call rotation, respond to production incidents, and carry work through root-cause analysis and durable remediation.
Broad infrastructure ownership: This is not a narrow CI/CD or cloud-administration role. You will work across GCP, AWS, Azure, Kubernetes, developer tooling, networking, security, and reliability.
Hands-on engineering required: The role is for a builder who can write automation, develop Terraform modules, troubleshoot production systems, and make technical decisions directly.
Global-team cadence: Regular working-hour overlap with U.S. Pacific Time is expected. Clear communication and dependable collaboration across time zones are core to the role.
Production GCP experience: Typically 5+ years in cloud, infrastructure, DevOps, SRE, or platform engineering, including hands-on ownership of GCP production environments.
Infrastructure-as-code and delivery fluency: Independent experience with Terraform, CI/CD systems such as GitHub Actions, Jenkins, Cloud Deploy, or equivalents, and production Kubernetes.
Cloud and networking depth: Strong knowledge of cloud architecture, distributed systems, VPCs, firewalls, load balancers, WAFs, and securing cloud environments.
Automation capability: Strong scripting or programming skills in Python, Go, Shell, or equivalent technologies, with a bias toward replacing manual work with repeatable systems.
Operational ownership: Experience handling complex incidents, conducting root-cause analysis, communicating clearly, and following through on improvements that prevent recurrence.
Turing is proud to be an equal opportunity employer. We do not discriminate on the basis of race, religion, color, national origin, gender, gender identity, sexual orientation, age, marital status, disability, protected veteran status, or any other legally protected characteristics. At Turing we are dedicated to building a diverse, inclusive and authentic workplace and celebrate authenticity, so if you’re excited about this role but your past experience doesn’t align perfectly with every qualification in the job description, we encourage you to apply anyways. You may be just the right candidate for this or other roles.
For applicants from the European Union, please review Turing's GDPR notice here.