Staff Site Reliability Engineer

Job description

This role is ideal for an engineer who enjoys solving complex technical challenges at scale, building automation, and improving the reliability of production systems. You will serve as a technical leader within the EPG SRE organization, partnering closely with software engineers, architects, and product teams to design, build, and operate world-class cloud services.

The ideal candidate exemplifies the philosophy of "if you have to do it more than once, automate it" and possesses a strong passion for continuous improvement, operational excellence, and software engineering.

Responsibilities

• Design, build, and operate large-scale cloud infrastructure and production services.
• Participate in an on-call rotation supporting highly available customer-facing systems.
• Lead incident response efforts and drive post-incident reviews focused on systemic improvements.
• Define, measure, and improve Service Level Indicators (SLIs), Service Level Objectives (SLOs), and error budgets.
• Partner with engineering teams to improve service availability, scalability, performance, and resilience.
• Continuously improve observability through metrics, logging, tracing, dashboards, and alerting.

Requirements

• Develop software, automation, and infrastructure using Go, Python, Terraform, and related technologies.
• Eliminate operational toil through automation, tooling, and platform engineering.
• Improve deployment safety and operational workflows through CI/CD and GitOps practices.
• Collaborate on modernizing existing workloads and aligning them with evolving platform capabilities.
• Build self-service platforms, operational guardrails, and automation that improve developer velocity while maintaining reliability and security.
• Lead complex reliability initiatives spanning multiple engineering teams.
• Guide engineers in adopting operational best practices and reliability engineering principles.
• Mentor engineers through technical collaboration, design reviews, incident analysis, and knowledge sharing.
• Influence architecture and operational decisions through data-driven recommendations and engineering expertise.
• Drive projects from conception through production rollout and long-term operational ownership.
• Explore and apply AI-assisted engineering techniques to improve operational efficiency, incident response, troubleshooting, and automation.
• Identify opportunities to leverage emerging technologies to reduce toil and improve engineering productivity.
• Strong experience operating large-scale production services in AWS and/or GCP.
• Deep expertise with Kubernetes in production environments.