below marketmost similar roles pay hereabove market
This listing doesn't post a salary. Most similar roles pay
$142,500–$214,000.
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
1226 open roles
on FindRole.
Listed pay typically runs
$156,750–$215,000
across 5 roles with salary data.
As a Site Reliability Engineer III within the Chief Data & Analytics Office AI/ML & Data Platforms team, you will solve complex business problems by configuring, maintaining, and optimizing applications and their associated infrastructure. You will independently decompose and iteratively improve existing solutions, ensuring end-to-end operations, availability, reliability, and scalability. Your daily work involves implementing infrastructure, configuration, and network as code, while collaborating with software engineers to develop automated continuous integration and continuous delivery pipelines. You will utilize technologies including Databricks, Snowflake, AWS, Kubernetes, Python, PySpark, Java/Spring Boot, and .Net. Additionally, you will use enterprise-authorized AI capabilities for incident triage and troubleshooting. Core competencies include managing SLIs, SLOs, and error budgets, as well as utilizing observability tools like Grafana, Dynatrace, Prometheus, Datadog, and Splunk.
What does a Site Reliability Engineer earn in California?
Median $202800 from 62 postings across 16 companies.
Configure, maintain, monitor, and optimize applications and cloud infrastructure to improve reliability and scalability.
Implement infrastructure, configuration, and network as code for assigned platforms.
Develop and support AI/ML solutions to accelerate incident triage, troubleshooting, and post-incident analysis.
Use AI capabilities to identify patterns in operational signals and automate the resolution of recurring toil.
Design and implement automated continuous integration and continuous delivery pipelines for production environments.
Manage production incident calls and coordinate incident management coverage with cross-functional teams.
Monitor system health using telemetry tools like Grafana, Prometheus, and Datadog to meet SLIs and SLOs.
Perform root cause analysis and implement production changes to improve application availability.
What we're looking for
Formal training or certification on site reliability engineering concepts and 3+ years of applied experience.
Proficiency in site reliability culture, principles, and implementing SRE within platforms, including SLI/SLO/SLA and error budgets.
Proficiency in at least one programming language such as Python, Java/Spring Boot, or .Net.
Proficiency in Python or PySpark for AI/ML modeling and automation to reduce operational toil.
Working knowledge of using enterprise-authorized AI capabilities to support SRE workflows with strong validation habits and data sensitivity awareness.
Proficient knowledge of software applications and technical processes, including hands-on experience in system design, resiliency, testing, and disaster recovery.
Experience in observability using tools such as Grafana, Dynatrace, Prometheus, Datadog, and Splunk.
Experience with CI/CD tooling, running production incident calls, and managing incident resolution.
Familiarity with container orchestration and networking technologies, plus the ability to work collaboratively in teams (preferred).
4+ years in an SRE or production support role with AWS Cloud, Databricks, Snowflake, or similar technologies (preferred).
Site Reliability Engineering
Python
Java
Spring Boot
.NET
EKS
EC2
Terraform
Kubernetes
Observability
CloudWatch
DNS
Route 53
ALB
NLB
mTLS
AI
Network as Code