Job Description & Details
This is a heavy-hitting Staff SRE role at Early Warning where you won't just be fighting fires—you'll be architecting the reliability and resilience for backbone financial services like Zelle and Paze. They are looking for a technical force multiplier who can build reusable tooling, define solid SLOs, and mentor engineering teams across complex distributed clusters without relying on pure authority. If you like dealing with high-throughput systems and reducing operational toil through smart automation rather than brute-force debugging, this is right in your wheelhouse.
What You'll Actually Be Doing
You'll spend your days partnering tightly with software engineering teams to bake reliability, performance, and observability straight into the development lifecycle from day one. You'll dive deep into clustered environments to squash recurring production bottlenecks, lead incident response for complex outages, and run blameless post-mortems that translate into actual architectural improvements. Expect to write automation and infrastructure-as-code to eliminate manual toil while pushing cross-service architectural standards that keep hundreds of millions of consumer transactions safe.
The Core Tech Stack
You need to bring serious chops in Python, Java, or Spring Boot, coupled with deep Linux/Unix fundamentals and AWS cloud architectures. Because Early Warning runs massive distributed data tiers, you must have hands-on production experience monitoring and tuning clustered environments like HBase, Kafka, Solr, and Hadoop via Cloudera Manager. On the observability front, fluency with tools like Splunk, AppDynamics, OpenTelemetry, and Grafana is non-negotiable for instrumenting metrics, traces, and robust alerting.
Interview Expectations
Expect the hiring panel to test your systems thinking by asking you to walk through how you would diagnose a cascading failure in a heavily distributed, asynchronous event-driven pipeline under heavy load. They want to see past generic answers and hear how you methodically isolate network partitions versus resource exhaustion using telemetry data. Another likely scenario will involve defending a cross-team architectural proposal where you have to balance speed-to-market against strict error budgets and high availability SLAs.
Application Advice
To get past the ATS, your resume needs to explicitly highlight terms like SLOs, error budgets, distributed systems troubleshooting, and Infrastructure as Code alongside your cloud and big-data stack experience. Don't just list technologies—use bullet points that quantify your impact, such as how you reduced MTTR, scaled clusters, or engineered reusable automation patterns that multiplied the output of your engineering peers.
