Software Engineer III — Asset & Wealth Management (AM Services) — New Jersey (Onsite)

J.P. Morgan Asset & Wealth Management delivers industry-leading investment management and private banking solutions. Asset Management provides individuals, advisors and institutions with strategies and expertise that span the full spectrum of asset classes through our global network of investment professionals. Wealth Management helps individuals, families and foundations take a more intentional approach to their wealth or finances to better define, focus and realize their goals.​

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 Asset & Wealth Management (AM Services), 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, enabling innovative investment and holdings capabilities through a unified services ecosystem with standardized data models and reusable components.

Job 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 and services that integrate with appropriate systems.
• Works independently across multiple applications/technologies, contributing to backend and full-stack delivery across distributed systems (e.g., microservices and service integrations).
• Produces architecture and design artifacts for complex applications while being accountable for ensuring design constraints are met by software code development.
• Applies knowledge of tools within the Software Development Life Cycle toolchain to improve delivery outcomes (e.g., CI/CD, automated testing, code review, observability).
• 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.
• Uses data as part of the software development process by gathering, analyzing, synthesizing, and developing reporting/visualizations from large, diverse data sets; identifies hidden problems and patterns and uses insights to drive improvements to coding hygiene and system architecture.
• Participates in an on-call/support rotation (primarily during business hours) and drives timely incident resolution and root-cause remediation.
• Collaborates effectively with stakeholders and partner teams; communicates clearly and incorporates feedback to drive iteration and delivery in an agile environment.
• Continues ongoing skill development and applies growth in proficiency across more than one technical area/discipline.

Required qualifications, capabilities, and skills

• Formal training or certification on software engineering concepts, or equivalent practical experience, and minimum 3+ years of 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 one or more modern programming languages and database querying languages (e.g., Java, SQL).
• Experience with distributed systems concepts and building services in patterns such as microservices and RESTful APIs.
• Overall knowledge of the Software Development Life Cycle and agile delivery practices.
• Hands-on experience using enterprise-authorized AI-assisted software development tools within the work environment, 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.

Preferred qualifications, capabilities, and skills

• Familiarity with common enterprise frameworks and platforms (e.g., Spring, messaging/streaming such as Kafka, cloud platforms such as AWS).
• Experience with relational databases such as Oracle and/or PostgreSQL.
• Familiarity with modern front-end technologies (helpful for full-stack scope).