Software Engineer III - Backend

JPMorganChase•Palo Alto, CA

About The Position

As a Software Engineer III at JPMorganChase within the Commercial & Investment Bank Digital & Platform Services team, you will serve as a seasoned member of an agile team designing and delivering secure, stable, scalable technology products. You will carry out critical technology solutions across multiple technical areas and business functions in support of the firm’s business objectives. The role focuses on designing, building, testing, and operating backend services and APIs using Java and Spring Boot. You will work with OpenAPI contracts, Kafka-based event-driven integrations, SQL, scripting, cloud environments, and containerization. You will also apply SDLC practices and enterprise-authorized AI coding tools to improve quality and productivity, while validating generated outputs through review, testing, and secure coding standards. This position is subject to Section 19 of the Federal Deposit Insurance Act. An employment offer is contingent on JPMorganChase’s review of criminal conviction history, including pretrial diversions or program entries.

Requirements

Formal training or certification in software engineering concepts and at least 3 years of applied experience.
Strong backend experience, including hands-on system design, application development, testing, and operational stability.
Hands-on expertise in Java and Spring Boot, including REST services, dependency injection, testing patterns, and performance tuning.
Experience designing and implementing APIs and defining contracts using OpenAPI Specification.
Working experience with AWS and/or Azure cloud technologies and cloud-native engineering practices.
Hands-on experience with Docker/containerization and deployment best practices.
Experience with Kafka, including producers and consumers, event-driven architecture patterns, and reliability considerations.
Proficiency in SQL and at least one scripting language for automation, troubleshooting, and data analysis.
Hands-on experience using enterprise-authorized AI-assisted software development tools at work, with the ability to evaluate, validate, and refine generated outputs for correctness, performance, and security.
Understanding of responsible AI use in engineering workflows, including data sensitivity, secure handling of inputs and outputs, and adherence to resiliency and security expectations; ability to guide peers in safe and effective use.
Knowledge of SDLC and agile practices, including CI/CD, application resiliency, and security.

Nice To Haves

Familiarity with modern backend technologies, patterns, and frameworks beyond core Spring Boot.
Exposure to the broader cloud-native ecosystem, including observability, infrastructure-as-code concepts, managed services, and security controls.
Basic front-end knowledge, such as UI integration patterns, web fundamentals, or modern JavaScript frameworks.

Responsibilities

Execute end-to-end software solutions through design, development, testing, and technical troubleshooting, developing scalable solutions and breaking down complex technical problems.
Create secure, high-quality production code and maintain reliable services and algorithms that integrate with dependent systems.
Design and build backend services and APIs using Java and Spring Boot, following clean architecture, performance, resiliency, and security best practices.
Define and implement API contracts using OpenAPI Specification (Swagger), ensuring consistent versioning, backward compatibility, and a strong consumer experience.
Use enterprise-authorized AI coding assistant tools to improve code quality, delivery speed, and productivity; validate outputs through peer review, automated testing, and secure coding standards.
Contribute reusable AI-assisted engineering patterns and learnings to improve team effectiveness.
Apply expertise across the SDLC toolchain, including CI/CD, automation, observability, and operational readiness, to improve delivery outcomes and reliability.
Produce architecture and design artifacts for complex applications and ensure design constraints are correctly implemented in code.
Build and maintain Kafka event-driven and streaming integrations, including topic design, message schemas, consumer groups, and reliability patterns.
Use SQL and scripting for development, troubleshooting, automation, and operational analysis.
Build, deploy, and operate services in AWS and/or Azure cloud environments; troubleshoot production issues and optimize cost, performance, and stability.
Use Docker and containerization, with related orchestration patterns where applicable, to provide consistent build and runtime environments.