Software Engineer III (Full Stack)

JPMorgan Chase & Co.; New York (NY); On-site; USD 120,000 - 180,000; Full time

Job summary

JPMorganChase is seeking a Software Engineer III to join a seasoned agile team within Global Banking, Commercial & Industrial Lending. You will design and deliver trusted, scalable technology products in a secure environment, contributing to architectural artifacts and data-driven improvements.

You will work with enterprise SDLC tools, emphasize responsible AI usage, and collaborate across business functions to advance code quality and system resilience.

Qualifications

• Formal training or certification on software engineering concepts and 3+ years applied experience.
• Hands-on practical experience in system design, application development, testing, and operational stability.
• Experience in developing, debugging, and maintaining code in a large corporate environment with Java and Python programming languages and database querying languages.
• Hands-on experience using enterprise-authorized AI-assisted software development tools with demonstrated ability to critically evaluate outputs for correctness, performance, and security.
• Understanding of responsible AI use in engineering workflows, including data sensitivity considerations and secure handling of inputs/outputs.
• Overall knowledge of the Software Development Life Cycle.
• Solid understanding of agile methodologies such as CI/CD, Application Resiliency, and Security.

Responsibilities

• Executes software solutions, design, development, and technical troubleshooting with ability to think beyond routine.
• Creates secure and high-quality production code and maintains algorithms that run synchronously with appropriate systems.
• Leverages enterprise-authorized AI coding assist tools to improve code quality, delivery speed, and productivity across complex deliverables.
• Applies knowledge of SDLC tools to improve automation.
• Produces architecture and design artifacts for complex applications and ensures design constraints are met.
• Gathers, analyzes, and visualizes data for continuous improvement of software applications.
• Proactively identifies hidden problems and patterns in data to drive improvements.

Skills

Java

Python

CI/CD

SQL

Education

Software engineering training or certification

Tools

AI-assisted development tools

Job description

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 Global Banking, Commercial & Industrial Lending division, 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.

Job responsibilities

• Executes software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or breakdown technical problems
• Creates secure and high-quality production code and maintains algorithms that run synchronously with appropriate 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.
• 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
• Proactively identifies hidden problems and patterns in data and uses these insights to drive improvements to coding hygiene and system architecture

Required qualifications, capabilities, and skills

• Formal training or certification on software engineering concepts and 3+ years applied experience
• Hands-on practical experience in system design, application development, testing, and operational stability
• Experience in developing, debugging, and maintaining code in a large corporate environment with Java and Python 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.
• Overall knowledge of the Software Development Life Cycle
• Solid understanding of agile methodologies such as CI/CD, Application Resiliency, and Security

Preferred qualifications, capabilities, and skills

• Strong interpersonal and communication skills, with the ability to partner effectively with bankers and translate complex technical concepts into compelling business narratives
• Demonstrated storytelling and presentation skills, with experience communicating insights to both technical and non-technical audiences
• Genuine curiosity and enthusiasm for AI and emerging technologies, including hands‑on experience with generative AI tools and prompt engineering
• Comfort leveraging AI-assisted development approaches, including rapid prototyping, AI-enabled coding workflows, and experimentation with new technologies