Backend Java Software Engineer III

JPMorgan Chase & Co.•Palo Alto, CA

13h•$133,000 - $185,000

About The Position

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 JPMorganChase within the Commercial and Investment Bank Digital & Platform Services, you are an integral part of an agile team dedicated to enhancing, building, and delivering trusted, market-leading technology products in a secure, stable, and scalable manner. As a core technical contributor, you will be responsible for implementing critical technology solutions across multiple technical domains, supporting various business functions to achieve the firm’s business objectives.

Requirements

Formal training or certification on software engineering concepts and 3+ years applied experience
Expertise in Java technologies/frameworks such as Spring/Spring Boot, and REST based services
Proficiency in Unix/Linux environments, ability to navigate the system, investigate processes and logs
Hands-on practical experience in system design, application development, testing, and operational stability
Proficiency in Java/JEE and REST APIs, Web Services and experience in building event-driven Micro Services and Kafka streaming.
Experience with using/managing AWS Services in public cloud infrastructure
Experience in developing, debugging, and maintaining code in a large corporate environment with one or more modern programming languages and database querying languages
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 effective usage within team practices

Nice To Haves

Experience with AI-powered development tools such as GitHub Copilot, Claude Code, or similar coding assistants to accelerate development workflows
Experience with modern front-end technologies/frameworks, specifically React, to build modern user interfaces

Responsibilities

Executes software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems
Creates secure and high-quality production code and maintains algorithms that run synchronously with appropriate systems
Produces architecture and design artifacts for complex applications while being accountable for ensuring design constraints are met by software code development
Gathers, analyzes, synthesizes, and develops visualizations and reporting from large, diverse data sets in service of continuous improvement of software applications and systems
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.
Drives adoption and governance of approved AI-assisted engineering practices across teams to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test acceleration, release readiness, incident/root-cause analysis), while establishing measurable validation standards (secure coding, peer review, automated testing) and promoting reuse of proven patterns and automation within the SDLC/TLM toolchain.