Senior Site Reliability Engineer

Responsibilities

• Design and implement infrastructure and tools that empower our product teams to rapidly and securely iterate, emphasizing reliability and automation.
• Influence the strategic direction of our infrastructure and operational practices, ensuring that we are well-positioned to scale and support our growing organization.
• Take a proactive role in the resolution of production issues, ensuring that we are well-prepared to handle incidents and that we learn from them in a blameless manner.
• Work closely with product teams on crucial initiatives such as production deployments, release management, and incident handling, aiming for seamless operations.
• Offer technical expertise and input to support the continual adoption and modernization of our platform and infrastructure.
• Build and deploy AI-powered tooling (autonomous coding agents, LLM-assisted CI/CD, automated incident triage) that makes the engineering org more productive. Think: sandboxed environments where agents can write, test, and verify code without human babysitting.
• Foster a culture of continuous learning and improvement, encouraging constructive review and adaptation processes.

Your Experience & Qualifications

• Kubernetes expertise, with a strong understanding of its core concepts and the ability to manage and maintain clusters.
• Expertise within modern cloud native tools, e.g. ArgoCD for GitOps, Terraform/Crossplane for IaC, and the Grafana LGTM stack (Loki, Grafana, Tempo, Mimir) for observability.
• 3-5 years of experience in using Infrastructure as Code and tools for cloud provisioning - Must
• 3-5 years of practice in development and scripting in languages like Go, Python, or similar - Must
• Proficient in both written and spoken English, with exceptional communication abilities.
• Expertise when it comes to Linux environments, containerization, and cloud technologies.
• Comprehensive knowledge of production management concepts for distributed systems.
• A history of 3-5 years in operational roles, overseeing production settings.
• AI fluency. You use AI coding tools daily and have opinions about what works. More importantly, you can build and deploy LLM-powered developer tooling and autonomous agents, not just consume them. We want someone who thinks about how to make an entire engineering team more productive with AI.
• Networking knowledge: bonus points for service mesh experience, platform engineering and cross-cloud networking.
• Familiarity with the Ethereum ecosystem, staking, and blockchain technologies - Advantage.

Conditions

• Salary: $82k - $112k estimated.