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Lead Software Engineer – Cloud Quality Engineering – Java / AWS

JPMorgan Chase

Lead Software Engineer – Cloud Quality Engineering – Java / AWS

JPMorgan Chase

New York, NY, United States, US

·

On-site

·

Full-time

·

2mo ago

Job Description

We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible.

As a Vice President, Software Engineer at JPMorgan Chase within the Cloud Quality Engineering team, you will promote the strategy, execution, and delivery of automated quality solutions for our cloud-native platforms.

Job Responsibilities

  • Lead and inspire a team of software and QA engineers, fostering a culture of innovation, collaboration, and continuous improvement.
  • Define and execute the quality engineering strategy for cloud-native applications, aligning with firmwide technology goals.
  • Architect and oversee the development of automated test frameworks and solutions using Java and Spring Boot.
  • Drive adoption of service virtualization (Wiremock, Hoverfly, Lisa) and REST API test automation across the organization.
  • Guide technical delivery for UI/mobile automation, database, ETL, and batch testing processes.
  • Integrate AWS services (EC2, S3, Lambda, etc.) and Kafka messaging into enterprise automation pipelines.
  • Establish performance testing standards and oversee execution using JMeter, Blaze Meter, or similar tools.
  • Partner with senior stakeholders in Technology and Business to embed automation into CI/CD workflows and deliver high-quality solutions.
  • Represent the team in technical forums, contributing to best practices and technology strategy across the firm.

Required Qualifications, Capabilities, and Skills

  • Formal training or certification in Software Engineering concepts and 5+ years applied experience, with a focus on automation, cloud, and quality.
  • Demonstrated leadership experience managing engineering teams and driving strategic initiatives.
  • Deep expertise in Java (Spring Boot), AWS cloud services, and REST API automation.
  • Experience with service virtualization tools (Wiremock, Hoverfly, Lisa).
  • Experience with one or more of the following: Kafka messaging, performance testing (JMeter, Blaze Meter), UI/mobile automation (Selenium, Appium), database/ETL/batch automation, CI/CD tools (Jenkins, Git).
  • Excellent communication, stakeholder management, and collaboration skills.

Preferred Qualifications, Capabilities, and Skills

  • Python programming experience.
  • Exposure to AWS Bedrock, Sagemaker, and LLM model workflows.
  • Familiarity with agentic workflows (Langgraph, Langchain) and MCP servers.
  • Experience with Docker, Kubernetes, or other containerization technologies.
  • Knowledge of cloud monitoring/logging (CloudWatch, ELK stack).
  • Understanding of cloud security best practices.

JPMorgan Chase is an equal opportunity employer, committed to diversity and inclusion. If you are passionate about leading teams, driving innovation, and delivering reliable systems at scale, we invite you to join our Cloud Quality Engineering team and help shape the future of technology at the firm.

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About JPMorgan Chase

JPMorgan Chase

JPMorgan Chase is a multinational investment bank and financial services company that provides banking, investment, and asset management services globally. It is one of the largest banks in the United States by assets and market capitalization.

300,000+

Employees

New York City

Headquarters

Reviews

4.2

10 reviews

Work Life Balance

4.2

Compensation

4.3

Culture

4.5

Career

4.4

Management

4.1

75%

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Pros

Good pay and benefits

Work-life balance

Career advancement opportunities

Cons

Heavy workload at times

Career advancement takes time

Pay could be better in some roles

Salary Ranges

47 data points

Junior/L3

Mid/L4

Senior/L5

Junior/L3 · Analyst

21 reports

$126,500

total / year

Base

$110,000

Stock

-

Bonus

-

$95,450

$155,250

Interview Experience

4 interviews

Difficulty

2.8

/ 5

Duration

14-28 weeks

Interview Process

1

Application Review

2

HireVue Video Interview

3

Technical/Behavioral Assessment

4

Final Interview Round

5

Offer Decision

Common Questions

Behavioral/STAR

Technical Knowledge

Past Experience

Culture Fit

Case Study