Software Engineer III (Full Stack
Job in
Jersey City, Hudson County, New Jersey, 07310, USA
Listed on 2026-08-22
Listing for:
JPMorgan Chase
Full Time
position Listed on 2026-08-22
Job specializations:
-
Software Development
DevOps, Java Developer, Cloud Engineer - Software, Software Engineer
Job Description & How to Apply Below
Software Engineer III
We have an exciting and rewarding opportunity for you to take your software engineering career to the next level. As a Software Engineer III at JPMorgan
Chase within the Audit Technology, you serve as a seasoned member of an agile team to design and deliver trusted market-leading technology products in a secure, stable, and scalable way. You are responsible for carrying out critical technology solutions across multiple technical areas within various business functions in support of the firm's business objectives.
- Design, build, test, deploy, and maintain enterprise applications for Internal Audit in close collaboration with business and customer stakeholders.
- Develop cloud-native microservices (Java and Python), including defining service contracts (REST APIs) and integrating with internal and third-party services.
- Build and enhance rich client user experiences using React and modern web engineering practices.
- Deploy services to container-based runtime environments and support releases to private/public cloud environments (AWS preferred).
- Create proof of concepts with new frameworks and libraries, identify best practices, and adapt quickly to evolving requirements.
- Perform design reviews and peer code reviews, and promote code quality standards (readability, testing, security, resiliency, maintainability).
- Build and maintain CI/CD pipelines and automated release processes, including promoting application packages across environments.
- Participate in Scrum ceremonies, technical reviews, and continuous improvement efforts for configuration management, deployment, and operational readiness.
- Leverages enterprise-authorized AI coding assist tools within the work environment to improve code quality, delivery speed, and productivity across complex deliverables (e.g., code generation/refactoring, unit test creation, documentation), while validating outputs through peer review, automated testing, and secure coding standards; contributes learnings and reusable patterns to improve broader team effectiveness.
- 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.
- Support operational stability by contributing to monitoring, incident triage, root-cause analysis, and preventative fixes.
- Formal training or certification on software engineering concepts and 3+ years applied experience
- Demonstrated experience building distributed applications using Java 8+ with Spring Boot/Spring and RESTful microservices.
- Demonstrated experience developing and maintaining services or automation in Python in a large enterprise environment.
- Working knowledge of modern frontend development with React and JavaScript/Type Script, including API integration patterns.
- Experience building and operating software using CI/CD practices (automated builds, tests, quality checks, packaging, deployment, and environment promotion).
- Experience with containerization and orchestration (Docker, ECS and/or Kubernetes) and deploying to cloud environments (AWS preferred).
- Solid understanding of application resiliency and production readiness practices (logging/monitoring, alerting, performance, and operational support).
- Solid understanding of secure software development practices (authentication/authorization patterns, secrets management concepts, and vulnerability remediation).
- Strong problem-solving skills, ability to meet deadlines, and track record of delivering high-quality code.
- Hands-on experience using enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, test creation, troubleshooting, or documentation) with demonstrated ability to critically evaluate, validate, and refine AI-generated outputs for correctness, performance, and security.
- Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; ability to guide peers on safe and…
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