SRE Senior - Plataforma

Accountabilities: • 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:

• 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.

Benefits:

• 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.

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