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This listing doesn't post a salary. Most similar roles pay
$141,947–$216,250.
Based on 240 similar postings.
Employer
About JPMorgan Chase
JPMorgan Chase & Co. is a global financial services firm and one of the largest banks in the world, offering investment banking, commercial banking, asset management, and consumer financial services.
JPMorgan Chase currently has
1197 open roles
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As a Site Reliability Engineer II within the Corporate and Investment Bank Payments Technology Team, you will ensure system reliability by delivering end-to-end application and infrastructure service delivery. You will independently execute projects and collaborate with cross-functional teams to define SLOs, SLIs, and error budgets for production services. Daily responsibilities include incident management, root cause analysis, and designing Dynatrace instrumentation to monitor performance. You will utilize enterprise-authorized AI capabilities for troubleshooting and identifying reliability risks. Required skills include Java, Spring Boot, Apache Kafka, Oracle databases, and Liquibase. You must possess experience with Jenkins, Docker, Kubernetes, and scripting in Python, Bash, or Node.js. The role focuses on managing large-scale on-prem and public cloud environments, core networking, and observability tools like Splunk and Geneos within the payments domain.
What does a Site Reliability Engineer earn?
Median $187850 from 136 postings across 39 companies.
Deliver end-to-end application and infrastructure service delivery to ensure reliable business operations.
Define and maintain SLOs, SLIs, and error budgets for key production services.
Use enterprise-authorized AI to speed up incident triage, troubleshooting, and post-incident analysis.
Manage day-to-day operational processes including incident, problem, change, and event management.
Monitor production environments and build alerting mechanisms to detect incidents early.
Design and implement Dynatrace instrumentation to monitor performance and infrastructure health.
Identify recurring toil and reliability risks using AI to prioritize reuse-first improvements.
What we're looking for
Formal training or certification on software engineering concepts and 2+ years of applied experience.
Working knowledge of using enterprise-authorized AI capabilities for SRE workflows with strong validation habits and data sensitivity awareness.
Ability to assess AI-assisted operational recommendations for correctness, risk, resiliency, security, and auditability.
Experience with large-scale application/infrastructure across on-prem and public cloud environments, including core networking (DNS, TCP/IP, VPN, load balancing).
Hands-on observability expertise using tools like Dynatrace, Geneos, and Splunk, plus distributed tracing and log analysis.
Strong microservices engineering with Java and Spring Boot, including event-driven patterns using Apache Kafka.
Data layer skills including Oracle databases, GemFire/Geode distributed caching, Liquibase migrations, and SQL management.
DevOps proficiency in Jenkins-based CI/CD, Docker, Kubernetes, and scripting in Python, Bash/PowerShell, and Node.js.