Site Reliability Engineer III, GWCP (SaaS)

Location: Curitiba, Brazil

Company

hirify.global provides a cloud platform for property and casualty insurers, combining core insurance operations with digital, data, analytics, and AI products.

What you will do

• Design, build, and operate reliable, scalable infrastructure for a multi-tenant SaaS platform.
• Automate deployment, provisioning, and operational workflows across cloud infrastructure and applications.
• Develop internal tools, services, and frameworks that reduce manual operational effort.
• Build observability systems, define SLOs, and improve reliability metrics across production services.
• Lead or contribute to incident response, root cause analysis, blameless postmortems, and resilience improvements.
• Collaborate with development teams on system design, security, production readiness, documentation, and technical enablement.

Requirements

• Strong programming skills in Python or Go; Java/Spring Boot is an advantage.
• Deep experience with AWS and production systems operating at scale.
• Hands-on experience with Kubernetes, including EKS, Docker, Helm, CNI, Ingress, and Kubernetes primitives.
• Experience with Infrastructure as Code using Terraform, Terragrunt, or similar tools.
• Knowledge of Linux systems, networking, observability, incident management, CI/CD, and GitOps.
• Working knowledge of SSO, SAML, OAuth, identity providers, and security and compliance standards.

Nice to have

• Experience with Kafka, SQS, Aurora, RDS, Okta, KubeVela, or Crossplane.
• Bachelor’s degree in Computer Science or a related field, or equivalent experience.
• Experience supporting large-scale SaaS platforms.
• AWS or Kubernetes certifications and open-source contributions.

Culture & Benefits

• Work on a mission-critical cloud platform used by more than 540 insurers in 40 countries.
• Participate in a 24x7 follow-the-sun on-call rotation supporting critical production systems.
• Collaborate with distributed engineering teams in a culture focused on integrity, innovation, learning, and collegiality.
• Use AI and data-driven insights to improve engineering productivity and outcomes.