Site Reliability Engineer III, Machine Learning

JPMorgan Chase

Confirmed live yesterday Low trust

Quick summary

Work type: On-site
Location: Wilmington, DE
Employment: Full-time
Posted: 72 days ago
Freshness: Confirmed live yesterday
Nearby: 99+ roles within 25 mi

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Salary context

How this pay compares to similar roles

Similar $183k

$137k $245k

below market most similar roles pay here above market

This listing doesn't post a salary. Most similar roles pay $147,200–$219,131.

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.

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At a glance

TL;DR · Site Reliability Engineer III, Machine Learning

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As a Site Reliability Engineer III - Machine Learning within the Corporate Technology, Consumer & Community Banking Risk team, you will design and implement technical solutions to ensure the resilience and performance of critical applications. You will independently decompose existing systems, configure cloud infrastructure, and optimize platforms using code. Your daily responsibilities include implementing infrastructure, configuration, and network as code, managing automated continuous integration and continuous delivery pipelines, and monitoring service level objectives. You will utilize Python, Java/Spring Boot, or .Net alongside enterprise-authorized AI capabilities to accelerate incident triage and identify reliability risks. Key technical skills include experience with container orchestration, observability tools, telemetry collection, and networking technologies. You will also manage data and compute workflows using tools like Airflow, AWS Step Functions, Databricks, and Terraform Enterprise.

What does a Site Reliability Engineer earn?

Median $180200 from 121 postings across 36 companies.

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Skills

Site Reliability Engineering Python Java Spring Boot .NET AWS Terraform Infrastructure-as-Code Airflow AWS Step Functions Databricks GitOps Argo CD Flux OpenTelemetry REST APIs Monitoring Telemetry

What you'll do

Design and implement technical solutions to configure, maintain, monitor, and optimize applications and cloud infrastructure.
Decompose existing systems and iteratively enhance them to improve reliability and scalability.
Implement infrastructure, configuration, and network as code for assigned applications and platforms.
Develop and implement deployment and reliability approaches using automated CI/CD pipelines.
Use enterprise-authorized AI to accelerate incident triage, troubleshooting, and post-incident analysis while ensuring data security.
Identify patterns in operational signals using AI to prioritize reliability improvements tied to SLO outcomes.
Resolve complex problems proactively by using service level indicators and objectives before they impact customers.
Provide guidance on building level designs and supporting the adoption of SRE best practices within the team.

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 site reliability within applications or platforms.
Proficiency in at least one programming language such as Python, Java/Spring Boot, or .Net.
Working knowledge of using enterprise-authorized AI capabilities to support SRE workflows with strong validation habits and data sensitivity awareness.
Ability to validate AI-assisted operational recommendations before applying changes and following data sensitivity requirements.
Proficient knowledge of software applications and technical processes within a technical discipline like Cloud or AI.
Experience in observability, including white and black box monitoring, SLO alerting, and telemetry collection.
Experience with continuous integration and continuous delivery tooling, container orchestration, and networking technologies.
Experience orchestrating data/compute workflows (e.g., Airflow or AWS Step Functions) (preferred).
Familiarity with Databricks jobs, clusters, and workspace operations (preferred).
Infrastructure-as-Code experience with Terraform Enterprise exposure (preferred).
GitOps and configuration management exposure, such as Argo CD/Flux patterns (preferred).
Familiarity with OpenTelemetry or similar standards for metrics, logs, and traces (preferred).
AWS certification (preferred).

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