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 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, you will strengthen infrastructure, optimize tooling, deepen observability, streamline incident response, and elevate reliability standards. These actions empower teams to ship quickly and safely.
The base salary range for this full-time position is $189,000 - $232,000 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.
HOW you will create impact
- 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.
WHAT you'll do
- 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.
WHAT we're looking for
- Bachelor’s or master’s degree in Computer Science, Engineering, or a related field, or equivalent industry experience.
- 3+ years of experience in SRE, Software Engineering, Infrastructure Engineering, or a related role.
- Hands-on coding experience in Python, Go, or similar production-oriented programming languages.
- Experience operating production systems and contributing to reliability, observability, incident response, infrastructure, or automation improvements.
- Working knowledge of SLIs, SLOs, error budgets, MTTR, and how reliability data informs engineering tradeoffs.
- Experience using logs, metrics, dashboards, traces, and alerts to diagnose production issues.
- Experience with distributed systems concepts such as retries, backoff, timeouts, graceful degradation, capacity planning, and failure isolation.
- Experience improving alert quality, runbooks, incident processes, and follow-through after production issues.
- Ability to communicate clearly, write useful documentation, and explain reliability concepts in plain language.
- Experience using AI-assisted development tools such as GitHub Copilot, Cursor, ChatGPT, Claude, or similar tools as part of your software development or operational workflow.
- Interest in using AI-assisted workflows to reduce toil, accelerate investigation, improve infrastructure-as-code workflows, and strengthen operational practices.
- Interest in mentoring peers and growing your impact across teams over time.
#LI-Hybrid
A Note on AI in the Hiring Process: EarnIn may use Artificial Intelligence (AI)-powered tools during the hiring process, including tools that generate summaries or notes for interviewers, review resumes, assist with scheduling, or help identify themes across candidate responses and profiles for a given role. Final hiring decisions are made by human interviewers and hiring managers. If you have any concerns about the use of AI in our hiring process, please connect with your recruiter. With your consent, EarnIn may use AI tools to help transcribe or summarize interviews. Recordings are treated as confidential candidate data and are accessible only to authorized hiring personnel. Declining to be recorded will not negatively affect your candidacy or evaluation.
At EarnIn, we believe that the best way to build a financial system that works for everyday people is by hiring a team that represents our diverse community. Our team is diverse not only in background and experience but also in perspective. We celebrate our diversity and strive to create a culture of belonging. EarnIn does not unlawfully discriminate based on race, color, religion, sex (including pregnancy, childbirth, breastfeeding, or related medical conditions), gender identity, gender expression, national origin, ancestry, citizenship, age, physical or mental disability, legally protected medical condition, family care status, military or veteran status, marital status, registered domestic partner status, sexual orientation, genetic information, or any other basis protected by local, state, or federal laws. EarnIn is an E-Verify participant.
EarnIn does not accept unsolicited resumes from individual recruiters or third-party recruiting agencies in response to job postings. No fee will be paid to third parties who submit unsolicited candidates directly to our hiring managers or HR team.