EarnIn
Staff Site Reliability Engineer
Mountain View, US · Staff+ · Full-time
Sponsorship not specified$252k-$308kDetected 50 days ago
PythonGoDynamoDBAWSCloud PlatformsKubernetesTerraformDatadogSite Reliability EngineeringKafkaLLMsAgentic AIIncident ResponseComplianceLeadershipCommunicationMentoring
About the role
- We're growing fast and are excited to continue bringing world-class talent onboard to help shape the next chapter of our growth journey.
- 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.
Responsibilities
- Lead high-severity incident response as IC.
- Build AI-driven alert correlation and triage that reduces noise and accelerates root-cause identification.
- Drive adoption of AI-generated postmortems that surface systemic patterns and automatically track corrective actions through to completion.
- Build AI agents that draft runbook responses, pull relevant context from Datadog, incident.io, and Slack during pages, and recommend remediation steps, so on-call engineers spend less time deciding and searching.
- Partner with product engineering to embed AI-assisted investigation, alerting, and production readiness into their workflows.
- Make AI tooling the default path for every team that owns a service, not an SRE-only capability.
- Guide service designs for graceful degradation, failure isolation, and capacity planning across EarnIn's AWS footprint (EKS, Kafka, DynamoDB, RDS, SQS).
- Coach engineers on reliability practices, run design and incident reviews, and build documentation and tooling that makes reliability knowledge accessible.
- Strong software engineering ability in Python, Go, or similar languages. You build tools and automation, not just dashboards.
- HOW you will create impact
Requirements
- 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.
- Significant expertise with SLIs, SLOs, error budgets, incident command, blameless postmortems, and recurrence prevention in large-scale distributed systems.
- 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.
- If you have any concerns about the use of AI in our hiring process, please connect with your recruiter.
Nice to have
- Experience in fintech, regulated environments, SOC 2, PCI, FinOps, or cost/performance tradeoffs in high-scale systems is a plus.
Skills
- Command high-severity incidents as Incident Commander and reinforce the systems, tools, and practices that simplify incident management.
- Transition teams from reactive paging to proactive reliability enhancement.
- Apply production data, incident learnings, and AI analysis to spot architectural risks before they recur.
- Produce documentation, tooling, and reusable patterns that unlock reliability knowledge and enable action.
Compensation
- The base salary range for this full-time position is $252,000-$308,000, plus equity and benefits.
Benefits
- The base salary range for this full-time position is $252,000-$308,000, plus equity and benefits.
- 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.
Company info
- WHAT we're looking for
- 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.
Visa & Work Authorization
- ildbirth, breastfeeding, or related medical conditions), gender identity, gender expression, national origin, ancestry, citizenship, age, physical or mental disability, legally protected medical condition, family care st
This listing is sourced directly from EarnIn's careers page and normalized into a canonical job model.