JP Morgan Chase

Runs a consumer bank and an investment bank

Site Reliability Engineer 3

Site Reliability EngineeringConfirmed live in the last 24 hours

Full-time$137.8k - $185kIn-person

About the Job

Requirements

Formal training or certification in site reliability engineering concepts and at least 3 years of applied experience.
Proficiency in site reliability culture and principles, including implementing site reliability practices within an application or platform and understanding service level indicators, service level objectives, service level agreements, and error budgets.
Proficiency in at least one programming language such as Python, Java with Spring Boot, or .NET, including Python or PySpark for AI/ML modeling and automation to reduce operational toil by building tools for repeated tasks.
Working knowledge of enterprise-authorized AI capabilities for SRE workflows, with validation habits and awareness of data sensitivity, including developing AI/ML solutions for troubleshooting and incident resolution.
Ability to validate AI-assisted operational recommendations before applying changes, escalate when uncertain, follow data-sensitivity requirements, and comply with risk controls and company-wide standards.
Proficiency in software applications and technical processes in a technical discipline such as cloud, AI, or Android, including hands-on experience in system design, resiliency, testing, operational stability, and disaster recovery.
Experience with observability, including white- and black-box monitoring, service-level-objective alerting, and telemetry collection using tools such as Grafana, Dynatrace, Prometheus, Datadog, and Splunk.
Experience with continuous integration and continuous delivery tooling, production incident calls, and managing incident resolution with cross-functional teams.
Familiarity with containers, container orchestration, and troubleshooting common networking technologies and issues.
Ability to collaborate in teams and build working relationships to achieve shared goals.

Responsibilities

Configure, maintain, monitor, and optimize applications and associated infrastructure through code and cloud infrastructure.
Decompose and iteratively improve existing solutions.
Share knowledge of end-to-end operations, availability, reliability, and scalability of the application or platform.
Guide and assist others in building appropriately scoped designs and gaining peer consensus where appropriate.
Support adoption of site reliability engineering best practices within the team, including technologies such as Databricks, Snowflake, AWS, and Kubernetes.
Collaborate with software engineers and teams to design, develop, test, and implement deployment and reliability approaches using automated continuous integration and continuous delivery pipelines, supporting application development and production environments.
Use enterprise-authorized AI capabilities to accelerate incident triage, troubleshooting, and post-incident analysis; validate outputs and handle operational data according to sensitivity and security requirements; develop and support AI/ML solutions for incident resolution.
Implement infrastructure, configuration, and network as code for applications and platforms in the role's remit.
Collaborate with technical experts, stakeholders, and team members to resolve complex problems, coordinate incident-management coverage, and address issues proactively using service level indicators and objectives before customer impact.
Apply enterprise-authorized AI capabilities to identify operational-signal patterns indicating reliability risks or recurring toil, prioritize reuse-first improvements tied to SLO outcomes, and support intelligent troubleshooting automation.
Work with partners to iteratively improve application availability, reliability, and scalability; participate in root cause analysis and implement production changes.
Recognize obstacles, identify improvements to solve business problems, and explore new technologies where appropriate.

Desired Qualifications

At least 4 years in an SRE or production support role with AWS Cloud, Databricks, Snowflake, or similar technologies.
AWS and Databricks certifications.

There’s nothing more exciting than being at the center of a rapidly growing field in technology and applying your skillsets to drive innovation and modernize the world's most complex and mission-critical systems.

As a Site Reliability Engineer III at JPMorgan Chase within the Chief Data & Analytics Office (CDAO) AI/ML & Data Platforms team,, you will solve complex and broad business problems with simple and straightforward solutions. Through code and cloud infrastructure, you will configure, maintain, monitor, and optimize applications and their associated infrastructure to independently decompose and iteratively improve on existing solutions. You are a significant contributor to your team by sharing your knowledge of end-to-end operations, availability, reliability, and scalability of your application or platform.

Job Responsibilities

Guides and assists others in the areas of building appropriate level designs and gaining consensus from peers where appropriate, supporting adoption of site reliability engineering best practices within your team, including modern technologies such as Databricks, Snowflake, AWS, and Kubernetes
Collaborates with other software engineers and teams to design, develop, test, and implement deployment and reliability approaches using automated continuous integration and continuous delivery pipelines, while supporting application development and production environments
Uses enterprise-authorized AI capabilities within the work environment to accelerate incident triage, troubleshooting, and post-incident analysis, validating outputs and handling operational data according to sensitivity and security requirements, including developing and supporting AI/ML solutions for incident resolution
Implements infrastructure, configuration, and network as code for the applications and platforms in your remit
Collaborates with technical experts, key stakeholders, and team members to resolve complex problems, coordinate incident management coverage, and proactively address issues using service level indicators and objectives before they impact customers
Applies enterprise-authorized AI capabilities within the work environment to identify patterns in operational signals that indicate reliability risk or recurring toil, prioritizing reuse-first improvements tied to SLO outcomes, and supporting intelligent automation for troubleshooting
Familiar with availability, reliability, scalability, and solutions in their applications and works with partners to improve these outcomes iteratively, including participation in root cause analysis and implementing production changes
Proactively recognizes road blocks and identifies improvements to solve business problems, including exploring new technologies where appropriate

Required qualifications, capabilities, and skills

Formal training or certification on site reliability engineering concepts and 3+ years applied experience
Proficient in site reliability culture and principles and familiarity with how to implement site reliability within an application or platform, including strong understanding of SLI/SLO/SLA and error budgets
Proficient in at least one programming language such as Python, Java/Spring Boot, and .Net, including Python or PySpark for AI/ML modeling and automation to reduce operational toil by building tools for repeated tasks
Working knowledge of using enterprise-authorized AI capabilities within the work environment to support SRE workflows with strong validation habits and awareness of data sensitivity, including developing AI/ML solutions for troubleshooting and incident resolution
Ability to validate AI-assisted operational recommendations before applying changes, escalating when uncertain and following data sensitivity requirements, while ensuring compliance with risk controls and company-wide standards
Proficient knowledge of software applications and technical processes within a given technical discipline (e.g., Cloud, AI, Android, etc.), including hands-on experience in system design, resiliency, testing, operational stability, and disaster recovery
Experience in observability such as white and black box monitoring, service level objective alerting, and telemetry collection using tools such as Grafana, Dynatrace, Prometheus, Datadog, Splunk, and others
Experience with continuous integration and continuous delivery tooling, along with experience running production incident calls and managing incident resolution in collaboration with cross-functional teams
Familiarity with container and container orchestration and troubleshooting common networking technologies and issues, along with ability to work collaboratively in teams and build meaningful relationships to achieve common goals

Preferred qualifications, capabilities, and skills

4+ years in an SRE or production support role with AWS Cloud, Databricks, Snowflake or similar Technologies.
AWS and Databricks certifications.

This position is subject to Section 19 of the Federal Deposit Insurance Act. As such, an employment offer for this position is contingent on JPMorganChase’s review of criminal conviction history, including pretrial diversions or program entries

Base Pay/Salary: Jersey City,NJ $137,750.00-$185,000.00; Palo Alto,CA $137,750.00-$185,000.00

About the Company

JP Morgan Chase

Runs a consumer bank and an investment bank

JPMorgan Chase runs the largest bank in the United States, which serves households and small businesses as Chase and large companies, governments, and investors as J.P. Morgan. During the 2008 financial crisis it bought the failing investment bank Bear Stearns and lender Washington Mutual, and in 2023 it took over First Republic Bank after regulators seized it. Chase takes deposits and earns interest on credit cards, mortgages, and car loans, while the investment side earns fees for advising on mergers, raising money for companies, trading stocks and bonds, and managing wealth. Formed in a 2000 merger, JPMorgan Chase traces its roots to 1799 and is based in New York City.

Company size: 10,001+
Company stage: IPO
Headquarters: New York City, New York
Founded: 1799

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