1h ago

New

SRE Senior - Plataforma

BrazilRemoteFull-timesenior

EngineeringDevops Engineer

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Quick Summary

Requirements Summary

Strong professional experience with Google Cloud Platform (GCP), particularly GKE, IAM, Pub/Sub, and BigQuery. Advanced knowledge of Kubernetes and distributed systems architecture.

Technical Tools

EngineeringDevops Engineer

We are looking for an experienced Senior Site Reliability Engineer to build and evolve an intelligent engineering platform that supports the entire software development organization. In this role, you will lead the development of an Agentic Engineering Platform, combining infrastructure automation, AI-powered agents, and developer experience to simplify complex engineering workflows. You will design scalable infrastructure, establish standardized development paths, and integrate observability and automation into the platform's core architecture. Working with Kubernetes, Google Cloud Platform, Terraform, and emerging AI technologies, you will help transform infrastructure operations into intelligent, increasingly autonomous processes. You will collaborate closely with SRE, FinOps, and product engineering teams to improve reliability, efficiency, and cost management. This is a high-impact opportunity to shape an AI-first engineering culture and redefine how modern platform reliability is delivered.

Ensure the reliability, availability, scalability, and performance of infrastructure components and the internal engineering platform.

Design, build, and continuously evolve the Agentic Engineering Platform, developing orchestration layers that understand developer intent, coordinate API executions, generate code, analyze data, and support AI-assisted troubleshooting.

Build and maintain standardized Golden Paths for CI/CD, integrating AI agents into workflows covering service templates, code reviews, approvals, and pull request merges while enforcing defined engineering guardrails.

Reduce service onboarding and setup time through standardized templates, automation, and improved developer experience.

Develop and implement comprehensive monitoring, observability, and alerting solutions as foundational components of the engineering platform.

Consolidate metrics, logs, traces, events, and infrastructure costs into reliable data sources that support intelligent automation and informed technical decisions.

Evolve and maintain Kubernetes infrastructure on Google Kubernetes Engine (GKE), focusing on sustainability, standardization, scalability, and intelligent automation.

Establish and improve incident management processes using AI-assisted detection, diagnosis, troubleshooting, and remediation workflows.

Design, implement, and maintain Infrastructure as Code (IaC) solutions using Terraform, including intelligent code generation, validation, automated rollback, recovery, and operational remediation.

Define, monitor, and improve Service Level Indicators (SLIs), Service Level Objectives (SLOs), and error budgets for platform components, establishing practices that can be replicated across product teams.

Support critical system migrations, environment segregation, and the deprecation of legacy technologies.

Collaborate closely with SRE Partner, FinOps, and product engineering teams to integrate reliability, cost efficiency, and platform capabilities across the organization.

Drive the adoption of AI-first engineering practices, promoting automation, standardization, operational excellence, and continuous improvement.

Requirements

~2 min read

Strong professional experience with Google Cloud Platform (GCP), particularly GKE, IAM, Pub/Sub, and BigQuery.

Advanced knowledge of Kubernetes and distributed systems architecture.

Solid experience with Infrastructure as Code (IaC), particularly Terraform.

Proficiency in observability tools and practices, including Prometheus, Grafana, Loki, Tempo, Thanos, OpenTelemetry, and Alertmanager.

Strong ability to analyze logs, metrics, traces, and performance issues across distributed systems.

Hands-on experience with GitHub Actions, ArgoCD, Helm, and GitOps practices, particularly within GKE environments.

At least two years of professional software development experience using Go or Python in production environments, with an emphasis on building high-quality, maintainable platform solutions rather than relying exclusively on configuration.

Practical experience deploying and operating LLM-based agents in production, including tool usage within agentic loops, Model Context Protocol (MCP), and orchestration through Vertex AI, Anthropic, or equivalent platforms.

Experience defining, monitoring, and managing SLOs, SLIs, and error budgets.

Hands-on experience with incident management, on-call rotations, troubleshooting, and post-incident reviews (post-mortems).

Strong data-driven and AI-first mindset, with the ability to leverage intelligence and automation to reduce manual effort and improve technical decision-making.

A platform-builder mindset, combining architectural thinking with hands-on development and implementation skills.

Excellent collaboration and communication skills, with the ability to work effectively across SRE, FinOps, and product engineering teams.

Strong sense of ownership, proactive problem-solving abilities, and motivation to continuously improve platform reliability and developer productivity.

Nice to have:

Previous experience building internal developer platforms (IDPs), Golden Paths, or developer experience (DevEx) solutions.

Significant contributions to observability initiatives, toil reduction, or operational automation projects.

Experience working in multi-cloud environments or organizations operating large-scale, high-traffic systems.

Familiarity with declarative infrastructure management and advanced GitOps practices.

Experience designing intelligent automation workflows that combine AI agents with infrastructure operations.

What We Offer

~2 min read

Fully remote work model, with the flexibility to work from anywhere in Brazil.

Opportunity to build and shape an innovative Agentic Engineering Platform.

Exposure to advanced technologies, including AI agents, LLMs, Kubernetes, cloud infrastructure, and distributed systems.

Opportunity to contribute to an AI-first engineering strategy and influence platform architecture across the organization.

High level of technical ownership and autonomy over strategic engineering initiatives.

Collaboration with experienced professionals across SRE, FinOps, infrastructure, and product engineering.

Continuous learning and professional development in a technically challenging environment.

Opportunity to work on large-scale systems supporting millions of users and extensive data infrastructure.

Inclusive and remote-first working environment.

How Jobgether works:

We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.

We appreciate your interest and wish you the best!

Why Apply Through Jobgether?

Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.

#LI-CL1

✓Fully remote work model, with the flexibility to work from anywhere in Brazil.

✓Opportunity to build and shape an innovative Agentic Engineering Platform.

✓Exposure to advanced technologies, including AI agents, LLMs, Kubernetes, cloud infrastructure, and distributed systems.

✓Opportunity to contribute to an AI-first engineering strategy and influence platform architecture across the organization.

✓High level of technical ownership and autonomy over strategic engineering initiatives.

✓Collaboration with experienced professionals across SRE, FinOps, infrastructure, and product engineering.

✓Continuous learning and professional development in a technically challenging environment.

✓Opportunity to work on large-scale systems supporting millions of users and extensive data infrastructure.

✓Inclusive and remote-first working environment.