Staff Site Reliability Engineer

📋 Job Overview

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.

🏢 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.

🎯 The Role

EarnIn’s products must deliver speed, reliability, resilience, and trust to community members who depend on them. As EarnIn grows, we cannot rely on heroics, tribal knowledge, manual investigation, or isolated SRE expertise. We must embed reliability practices that scale across product engineering teams, enhance customer experience, and enable rapid shipping without increasing operational risk.

This role exists to lead EarnIn’s next stage of reliability maturity: an AI-first operating model that uses AI to actively detect, investigate, respond to, learn from, and prevent production issues. As a Staff Site Reliability Engineer, you will guide technical direction for reliability across critical services, relying on AI-assisted workflows as key tools to reduce toil, speed incident response, improve production readiness, and enhance the operational quality of the engineering organization.

✅ Key Responsibilities

• Act as a Staff-level technical leader: define standards, architect solutions, mentor engineers, influence cross-team efforts, and construct reusable systems and practices that multiply your impact.
• You will embed AI-first thinking into reliability practices, leveraging AI to streamline alert triage, accelerate incident investigation, automate runbooks, retrieve operational knowledge, enhance postmortem quality, track corrective actions, quantify reliability with scorecards, detect capacity risks, and analyze architectural risks.
• You will maintain human ownership and engineering judgment at the center of operations. AI aids engineers by speeding context gathering, clarifying reasoning, and reducing repetition, but it does not replace accountability.
• Collaborate with SRE, product engineering, infrastructure, security, and leadership teams to embed reliability, making it easy to adopt and impossible to ignore.

📌 Required Qualifications

• 7+ years in SRE, Software Engineering, or Infrastructure Engineering with increasing scope and cross-org influence. Track record of KPI driven reliability and operational excellence improvements at scale.
• Demonstrated experience improving reliability and operational excellence at scale using clear KPIs such as MTTR, MTTD, alert quality, incident recurrence, SLO attainment, on-call health, or corrective-action completion.
• Shipped experience applying AI/LLMs to engineering or operational workflows, such as alert triage, runbook automation, incident investigation, postmortem drafting, remediation recommendation, operational knowledge retrieval, or agentic operations tooling.
• Significant expertise with SLIs, SLOs, error budgets, incident command, blameless postmortems, and recurrence prevention in large-scale distributed systems.
• Strong software engineering ability in Python, Go, or similar languages. You build tools and automation, not just dashboards.
• Deep observability experience with systems such as Datadog, CloudWatch, OpenTelemetry, or similar platforms, with a bias toward signal-heavy alerting designed for real human response.
• Strong infrastructure-as-code and cloud infrastructure experience, including Terraform, Kubernetes, AWS, and safe, reversible deployment practices.
• Practical experience using AI-assisted development tools such as Cursor, Claude Code, Copilot, ChatGPT, or similar tools to accelerate your own engineering work and model effective adoption for partner teams.

🎁 Benefits

The base salary range for this full-time position is $252,000-$308,000, plus equity and benefits. Our salary ranges are determined by role, level, and location. This is a hybrid position in Mountain View (Headquarters) and will require in-office work 2 days a week.