系统可靠性工程师（SRE）

This role sits within a high-impact MLOps environment, focused on ensuring the reliability, scalability, and performance of infrastructure that supports machine learning models and production data pipelines. You will be part of a collaborative and engineering-driven team, working on modern cloud-native systems in a fast-paced and continuously evolving context. The position involves direct contribution to the stability of critical platforms running on AWS and Kubernetes, with strong emphasis on automation, observability, and operational excellence.

Solid hands-on experience with Terraform for infrastructure as code. Strong knowledge of AWS cloud services and architecture. Intermediate experience with Kubernetes, including Helm and GitOps workflows. Experience working with GitLab CI/CD pipelines and version control workflows. Ability to troubleshoot networking in cloud environments (VPC, DNS, security groups, load balancers). Good understanding of Linux systems administration. Familiarity with observability tools such as Prometheus, Grafana, and Datadog. Strong analytical thinking and problem-solving skills in distributed systems environments. Clear communication skills and ability to collaborate in cross-functional teams. Proactive mindset with ownership and willingness to learn and grow in SRE/MLOps contexts.

Remote work model within Brazil. Flexible working arrangements. Competitive compensation package (based on experience). Health and dental insurance. Continuous learning and development opportunities. Exposure to large-scale cloud and machine learning infrastructure. Collaborative engineering culture focused on innovation and knowledge sharing. Career growth opportunities in SRE, DevOps, and MLOps domains. Inclusion in a diverse and supportive tech community.