Senior Site Reliability Engineer

About EarnIn As one of the first pioneers of earned wage access, our passion at EarnIn is building products that deliver real-time financial flexibility for those with the unique needs of living paycheck to paycheck. Our community members access their earnings as they earn them, with options to spend, save, and grow their money without mandatory fees, interest rates, or credit checks. We’re fortunate to have an incredibly experienced leadership team, combined with world-class funding partners like A16Z, Matrix Partners, DST, Ribbit Capital, and a very healthy core business with a tremendous runway. We’re growing fast and are excited to continue bringing world-class talent onboard to help shape the next chapter of our growth journey. WHY this role exists EarnIn’s community members rely on our products to perform consistently, respond promptly, and instill trust. Reliability goes beyond infrastructure; it shapes the customer experience. Product teams must deploy rapidly, but they must also develop systems that are observable, resilient, easy to operate, and safe to update. This role exists to elevate the reliability of EarnIn’s production systems while empowering engineering teams to advance swiftly with assurance. As a Senior Site Reliability Engineer, you will spearhead reliability enhancements that fortify services, streamline incident management, and foster sustainable on-call practices. This role can be remote anywhere in Mexico, or Hybrid with 2+ days a week in our Mexico City office. HOW you will create impact Act as a senior technical owner for reliability initiatives. Collaborate across systems, teams, and failure modes to strengthen how EarnIn designs, observes, deploys, and manages production services. You will combine software engineering fundamentals with reliability thinking. Rather than just responding to incidents, you will apply lessons learned to improve systems, alerts, runbooks, and ownership, reducing repeat failures. Leverage AI-assisted engineering practices, such as machine learning monitoring tools and anomaly detection systems, to minimize operational toil, accelerate investigations, refine infrastructure workflows, and enable teams to analyze production behavior more effectively. Mentor engineers and coach product teams to embed reliability practices that clarify, streamline, and safeguard their services. WHAT you will own Reliable system design Engineer and refine systems focusing on resilience, graceful degradation, capacity, and understanding failure modes. Collaborate with engineering teams to surface and address reliability risks during design, implementation, launch, and operation. Transform services to be simpler to debug, easier to operate, and more predictable under failure. SLOs, observability, and production signals Define and measure SLIs and SLOs that reflect real customer experience. Apply observability tools such as Datadog, CloudWatch, logs, metrics, traces, and APM to create signal-rich, noise-light operational visibility. Elevate alerting quality so pages drive action, reach the right people, and warrant human intervention. Incident lifecycle improvement Direct and optimize incident response practices from detection and triage to communication, resolution, postmortems, and follow-up. Extract incident learnings to implement lasting technical and process improvements. Guide teams to reduce repeated incidents and cultivate a quieter on-call environment. Operational tooling and AI-assisted leverage Develop or refine tooling that eliminates toil, accelerates root-cause analysis, and streamlines infrastructure-as-code workflows. Apply AI-assisted development and operational workflows responsibly to hasten investigations, enhance documentation, evolve runbooks, and automate repetitive engineering tasks. Help teams adopt practical AI-assisted workflows where they measurably improve quality, speed, or operational clarity. Mentorship and engineering enablement Coach engineers in reliability pra