EarnIn - Site Reliability Engineer II
Requirements
• A bachelors or masters degree in computer science or equivalent industry experience • 3+ years of experience in an SRE or Software Engineering role. • Hands-on coding experience in Python and/or Go. • Distributed Systems Expertise — Proven experience designing, operating, and shepherding large-scale distributed systems from design through production, including incident learnings that make on-call quieter over time. • Distributed Systems Expertise • Reliability Engineering Mindset — Deep fluency in SLOs, SLIs, error budgets, and MTTR — using them to drive decisions and explain tradeoffs, not just decorate dashboards. • Reliability Engineering Mindset • Observability & Incident Response — Treats observability as essential, not optional; stays calm under pressure; can diagnose incidents from logs and metrics and translate findings into durable process and technical improvements. • Observability & Incident Response • Cross-functional Communication — Able to work across technical and non-technical teams, reduce silos through documentation and runbooks, and explain reliability concepts in plain language. • Cross-functional Communication • Operational Tooling & AI Fluency — Selects the right tools for production management and leverages AI-assisted development to reduce toil, accelerate RCA, and streamline infrastructure-as-code workflows. • Operational Tooling & AI Fluency • Leadership & Mentorship — Can plan and lead strategic reliability initiatives across engineering, and invests in mentoring engineers as a high-leverage path to long-term reliability improvements. • Leadership & Mentorship
Responsibilities
• You will operate as a well-rounded SRE practitioner across production operations, observability, incident response, infrastructure-as-code, automation, and software engineering. • You will demonstrate growing independence in reliability work. You will not only follow existing playbooks, but also refine them. You will transform production learnings into better alerts, clearer runbooks, safer deployments, stronger observability, and more reliable services. • You will harness AI-assisted development and operational workflows to minimize toil, accelerate investigation, enhance documentation, and streamline infrastructure and reliability work. You will meticulously validate AI-generated output before applying it to production systems or operational workflows. • You will collaborate with product engineering and platform teams to implement, explain, and support reliability practices, ensuring they are practical, understandable, and actionable. • Design and improve systems with resilience and graceful degradation in mind. Plan for capacity and possible failure modes. • Define and measure SLOs and SLIs that reflect customer experience and help teams make better reliability tradeoffs. • Use observability tools such as Datadog, CloudWatch, logs, metrics, traces, and APM. Build signal-heavy, noise-light visibility into production systems. • Configure and improve alerting and routing through incident management workflows. Make sure pages are actionable, well-routed, and worth human attention. • Participate in incident response from detection and triage through communication, resolution, postmortems, and follow-up. • Continuously improve the incident lifecycle. Focus on better detection, clearer runbooks, stronger postmortems, and concrete remediations. • Construct or optimize infrastructure, reliability tooling, and automation that eliminate toil and ensure operational consistency. • Use AI-assisted tools to accelerate coding and documentation. Speed up root-cause exploration, runbook improvement, infrastructure-as-code workflows, and operational tasks. • Help engineering teams improve production readiness and deployment safety. Support service ownership and operational clarity. • Communicate reliability concepts clearly across technical and non-technical teams. • Document operational knowledge to reduce silos. Make it easier for engineers to respond with confidence. • Contribute to a culture where reliability is shared by SRE and product engineering teams.
Benefits
• EarnIn’s community members rely on our products to deliver reliability and trust when they need them most. Reliability shapes the product experience, not simply operational concerns. Every noisy alert, unclear runbook, fragile deployment, or repeated incident undermines customer trust and hinders engineering teams. • This role enables EarnIn to build and run production systems with greater resilience, clarity, and confidence. As a Site Reliability Engineer II, you will strengthen infrastructure, optimize tooling, deepen observability, streamline incident response, and elevate reliability standards. These actions empower teams to ship quickly and safely.
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