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EarnIn

Site Reliability Engineer

Mountain View, US$189k–$232kfull-timemidAdded today

About this role

EarnIn seeks a Site Reliability Engineer to strengthen production systems and build a resilient infrastructure foundation. You'll design reliable systems, define SLOs/SLIs, manage observability tooling, lead incident response, and collaborate with engineering teams to embed reliability practices across the organization.

What you'll do

  • Design and optimize systems for resilience, capacity planning, and graceful failure handling
  • Define, measure, and communicate SLOs/SLIs that guide reliability tradeoffs
  • Build observability solutions using Datadog, CloudWatch, logs, metrics, and APM tools
  • Manage alerting, incident routing, response, postmortems, and continuous improvement
  • Automate infrastructure and eliminate operational toil through code and tooling
  • Partner with engineering teams on production readiness, deployment safety, and service ownership

What they're looking for

  • Site Reliability Engineering practices and incident management
  • Python or Go programming for production systems
  • Observability platforms (Datadog, CloudWatch) and monitoring architecture
  • Infrastructure-as-Code and deployment automation
  • SLO/SLI definition and reliability metrics
  • Linux/Unix system administration and cloud infrastructure
  • Root cause analysis and postmortem facilitation
  • AI-assisted development tools

Benefits

  • Competitive base salary $189,000 - $232,000
  • Equity compensation
  • Hybrid work arrangement (2 days/week on-site in Mountain View)
  • Work with a well-funded fintech company backed by A16Z and Matrix Partners
  • Strong engineering culture focused on reliability and impact
  • Opportunity to shape infrastructure for millions of users
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EarnIn

EarnIn builds AI-powered financial products that enable users to access their earnings in real-time. The company is hiring Software Engineers to own features end-to-end, working with generative AI tools and collaborating across product and ML teams.

Website
earnin.com
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Likely interview questions

  • Walk us through a production incident you responded to—how did you approach triage, communication, and postmortem?
  • Describe your experience defining or refining SLOs and SLIs. How did they influence engineering decisions?
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