Drimva

JPMorgan Chase

Site Reliability Engineer III - Performance Engineer- Service now

$138K–$185K

San Francisco, CA · Full-time · Posted Sep 29, 2026

Experience
3+ years of applied SRE experience; 10+ years in technical support, software development, performance load testing, or professional services.

About the job

Owns and improves the reliability, performance, and operation of JPMorgan Chase’s ServiceNow platform, including incident response, automation, observability, and platform tuning.

What you'll do

  • Lead incident response and blameless post-mortems; define and improve SLIs, SLOs, error budgets, telemetry, and alerting.
  • Analyze ServiceNow performance across the stack and deliver stability, resiliency, and performance improvements, including JVM and database tuning.
  • Automate operational work and use enterprise-authorized AI capabilities to support incident analysis and identify reliability risks, validating outputs and protecting sensitive data.

What they ask for

  • Formal training or certification in site reliability engineering concepts and 3+ years of applied experience.
  • 10+ years in technical support, software development, performance load testing, or professional services.
  • Proficiency in at least one programming language; experience with scripting and debugging object-oriented code such as Java.
  • Strong RDBMS and performance-tuning experience, JVM performance tuning and troubleshooting, and expert-level understanding of web application stack components.

Nice to have

  • ServiceNow CSA (or higher) or prior ServiceNow architecture exposure.
  • Cloud/SaaS experience; Java heap dump analysis; ITSM/ITIL/CMDB fundamentals; server administration or browser/network troubleshooting tools.

Pay

San Francisco, CA: USD 137,750.00-$185,000.00 base salary

Tools

ServiceNow, Python, Java/Spring Boot, .Net, JavaScript, Perl, Unix shell, Windows PowerShell

AI focus

Use enterprise-authorized AI capabilities for incident triage, troubleshooting, post-incident analysis, and identifying reliability risks or recurring toil; validate recommendations and follow data-sensitivity requirements.

Model-written summary · the original posting is authoritative

First seen Oct 28, 2026 · Last verified Nov 5, 2026 (UTC)