Senior Site Reliability Engineer (Sre) - (Brazil)

Senior Site Reliability Engineer (SRE) - (Brazil)

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Position Overview

We are seeking an experienced Site Reliability Engineer (SRE) to join our team and help ensure the reliability, performance, and scalability of our GenAI SaaS platform.

As an SRE, you will bridge the gap between development and operations, implementing automation and best practices to maintain our service reliability objectives while supporting rapid innovation.

Key Responsibilities

Architect and maintain scalable, highly available infrastructure for our GenAI platform.

Design and implement robust monitoring, alerting, and observability solutions to proactively ensure system health and performance.

Automate deployment, scaling, and management of our cloud-native infrastructure, reducing toil and improving efficiency.

Define, measure, and improve Service Level Objectives (SLOs) and Service Level Indicators (SLIs) to deliver outstanding service quality.

Participate in on-call rotations and provide rapid response to production incidents, minimizing downtime and user impact.

Collaborate closely with development teams to build reliable, scalable, and efficient systems for complex AI workloads.

Lead incident response efforts, conduct thorough post-mortems, and champion continuous improvement initiatives.

Optimize infrastructure for performance, scalability, and cost-effectiveness—especially for high-demand AI workloads.

Implement and enforce security best practices across all systems and environments.

Create and maintain comprehensive documentation, including runbooks and knowledge base articles, to foster a culture of shared knowledge.

Required Qualifications

Bachelor's degree in Computer Science, Engineering, or related field, or equivalent practical experience.

5+ years of experience in DevOps, SRE, or similar roles.

Strong experience with cloud platforms (AWS, GCP, or Azure).

Proficiency in at least one programming / scripting language (Python, Go, Bash, etc.).

Hands-on experience with infrastructure as code tools (Terraform, CloudFormation, etc.).

Solid background in containerization technologies (Docker, Kubernetes).

Proven experience with monitoring and observability tools (Prometheus, Grafana, ELK stack, etc.).

Strong understanding of CI / CD pipelines and automation.

Exceptional troubleshooting and problem-solving skills and ability to troubleshoot complex systems.

Preferred Qualifications

Experience supporting AI / ML systems in production.

Knowledge of GPU infrastructure management and optimization.

Familiarity with distributed systems and high-performance computing.

Experience with database systems (SQL and NoSQL).

Certifications in cloud platforms (AWS, GCP, Azure).

Experience with chaos engineering and resilience testing.

Knowledge of security best practices and compliance requirements.

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