JP Morgan Chase

Runs a consumer bank and an investment bank

Manager of Software Engineering - Automation QA

Engineering LeadershipConfirmed live in the last 24 hours

Full-timeNo salary listedIn-person

About the Job

Requirements

Formal training or certification in software engineering concepts and at least 5 years of applied experience, plus coaching and mentoring experience.
Strong understanding of Asset and Wealth Management functioning and trading.
Strong hands-on experience with the AWS stack, including EC2, S3, Lambda, and CloudWatch.
Proficiency with performance-testing tools such as JMeter, LoadRunner, Gatling, and BlazeMeter; experience with CI/CD tools such as Jenkins and GitLab CI; and test orchestration experience.
Exposure to application performance monitoring tools such as AppDynamics and Dynatrace, and logging/monitoring platforms such as the ELK Stack, OpenSearch, Splunk, and Grafana.
Programming and scripting skills in Python, Java, Groovy, Node.js, and SQL, as well as big data skills and the ability to work across diverse technology at scale.
Experience leading responsible adoption of enterprise-authorized AI-assisted development and delivery tools across engineering teams, including defining review and validation practices, measuring outcomes, and ensuring secure data handling.
Understanding of responsible AI use in engineering workflows, including data sensitivity, resiliency and security implications, and governance expectations; ability to coach engineers on compliant and effective use.

Responsibilities

Build holistic quality engineering strategies for multi-year, multi-application programs.
Design, develop, and maintain reusable automated frameworks, tooling, and utilities, and build continuous integration automation capability.
Design, develop, and maintain automated performance-testing frameworks and utilities; implement and manage CI/CD pipelines for performance-test orchestration and automated result generation.
Execute load, stress, and scalability tests using JMeter, LoadRunner, Gatling, BlazeMeter, or similar tools.
Integrate and use monitoring tools, including application performance monitoring tools and AppDynamics, and logging platforms including the ELK Stack, OpenSearch, Splunk, and Grafana, for real-time analysis and reporting.
Collaborate with cross-functional teams to define performance requirements and ensure robust coverage; analyze test results, identify bottlenecks, and recommend optimizations.
Support pre- and post-deployment performance validation in AWS environments.
Manage approximately 6–8 technofunctional quality engineers.
Lead team adoption of enterprise-authorized AI-assisted engineering practices and SDLC/TLM automation to improve delivery speed, quality, and operational outcomes; set expectations for human validation, secure handling of inputs and outputs, and consistent use of reusable patterns across teams.
Apply knowledge of tools in the software development life cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve automation value and support capacity-unlock initiatives.
Lead multiple teams and manage day-to-day implementation activities by identifying and escalating issues and ensuring team work adheres to compliance standards, business requirements, and tactical best practices.

This is your chance to change the path of your career and guide multiple teams to success at one of the world's leading financial institutions.

As a Manager of Software Engineering at JPMorganChase within the Asset and Wealth Management organization, you lead multiple teams and manage day-to-day implementation activities by identifying and escalating issues and ensuring your team’s work adheres to compliance standards, business requirements, and tactical best practices.

Job responsibilities

Build holistic QE strategies around multi-year, multi application programs
Design, develop, and maintain reusable automated frameworks, tooling and utilities . Build CI automation capability
Design, develop, and maintain automated performance testing frameworks and utilities. Implement and manage CI/CD pipelines for performance test orchestration and automated result generation.
Execute load, stress, and scalability tests using tools such as JMeter, LoadRunner, Gatling, BlazeMeter, and similar.
Integrate and leverage monitoring tools (APM, AppDynamics) and logging platforms (ELK Stack, OpenSearch, Splunk, Grafana) for real-time analysis and reporting.
Collaborate with cross-functional teams to define performance requirements and ensure robust coverage.Analyze test results, identify bottlenecks, and recommend optimizations. Support pre- and post-deployment performance validation in AWS environments.
People management for around 6-8 technofunctional QEs
Leads team adoption of enterprise-authorized AI-assisted engineering practices and SDLC/TLM automation to improve delivery speed, quality, and operational outcomes, while setting expectations for human validation, secure handling of inputs/outputs, and consistent use of reusable patterns across teams.
Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation and support capacity unlock initiatives.

Required qualifications, capabilities, and skills

Formal training or certification on software engineering* concepts and 5+ years applied experience. In addition, demonstrated coaching and mentoring experience
Strong understanding of the AWM functioning and trading
Strong hands-on experience with AWS stack (EC2, S3, Lambda, CloudWatch, etc.
Proficiency in performance testing tools: JMeter, LoadRunner, Gatling, BlazeMeter etc. Experience with CI/CD tools (Jenkins, GitLab CI, etc.) and test orchestration.
Exposure to APM tools (AppDynamics, Dynatrace) and logging/monitoring platforms (ELK Stack, OpenSearch, Splunk, Grafana).
Solid programming/scripting skills (Python, Java, Groovy, NodeJS, SQL).
Excellent analytical, communication, and leadership abilities
Strong programming skills in Python, NodeJS, Java, Groovy, SQL, big data and an appetite to be able work on diverse technology at scale
Experience leading responsible adoption of enterprise-authorized AI-assisted development and delivery tools across engineering teams, including defining ways of working (review/validation expectations), measuring outcomes, and ensuring secure handling of data.
Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, resiliency/security implications, and governance expectations; ability to coach engineers on compliant and effective usage.

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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