Software Engineer III - UI / Experience Services Developer

JPMorganChase•Plano, TX

About The Position

As a Software Engineer III at JPMorganChase within Consumer & Community Banking (CCB), J.P. Morgan Wealth Management (JPMWM), you serve as a seasoned member of an agile team designing and delivering trusted, market-leading technology products in a secure, stable, and scalable way. The role focuses on building responsive UI components and Java-based experience services that incorporate agentic, LLM-driven workflows. You carry out critical technology solutions across multiple technical areas and business functions in support of the firm's business objectives. You build and maintain responsive user interfaces and the API/service layer supporting front-end experiences, primarily using Java, and integrate agentic capabilities into applications and user journeys. You also promote the effective use of enterprise-authorized AI-assisted engineering tools and practices, ensuring AI outputs are validated through peer review, automated testing, and secure coding standards. The role includes producing architecture and design artifacts, analyzing data to improve applications and systems, collaborating across product, design, and backend teams, and supporting quality and operational stability through debugging, testing, documentation, and engineering standards.

Requirements

3+ years of professional experience in UI development and experience services development.
Strong hands-on experience with Java for backend or service development, such as building RESTful services.
Exposure to agentic capabilities or LLM-driven workflows and integrating them into applications.
Basic SQL knowledge for simple queries used in validation and troubleshooting.
Practical experience in system design, application development, testing, and operational stability.
Experience developing, debugging, and maintaining code in a large corporate environment using one or more modern programming languages and database querying languages.
Demonstrated experience leading effective use of approved AI-assisted software development tools for coding, code review, test acceleration, and troubleshooting, including setting expectations for validating AI outputs for correctness, performance, and security.
Strong understanding of responsible AI use in engineering workflows, including data sensitivity, secure handling of inputs and outputs, and adherence to resiliency and security expectations.
Experience coaching engineers on safe, compliant adoption of AI-assisted development within delivery practices.
Overall knowledge of the Software Development Life Cycle.
Solid understanding of agile methodologies such as CI/CD, application resiliency, and security.
Strong problem-solving and communication skills, and ability to work effectively in an agile environment.

Nice To Haves

Foundational machine learning understanding, model integration, or experience with ML-enabled features.
Experience with Apache Spark for batch or stream processing, data pipelines, or large-scale data processing.
Experience with API design best practices, service reliability, observability, and performance optimization.
Familiarity with secure coding practices, including authentication/authorization, data handling, and input validation.
Familiarity with modern front-end technologies.
Exposure to cloud technologies.

Responsibilities

Design, develop, and troubleshoot software solutions, applying approaches beyond routine or conventional methods to solve technical problems.
Create secure, high-quality production code and maintain algorithms that run synchronously with appropriate systems.
Build and maintain responsive, user-friendly UI components and workflows, as well as Java-based experience services and APIs supporting front-end experiences.
Implement and integrate agentic capabilities, including workflow orchestration, tool/function calling patterns, guardrails, and state management for agent flows.
Use enterprise-authorized AI coding assistance tools to improve code quality, delivery speed, and productivity, validating outputs through peer review, automated testing, and secure coding standards.
Drive team adoption of enterprise-authorized AI-assisted engineering practices, establish consistent validation standards, and promote reusable patterns.
Use Software Development Life Cycle tools and automation capabilities to improve the value realized by automation.
Produce architecture and design artifacts for complex applications and ensure software development meets design constraints.
Gather, analyze, synthesize, and visualize diverse data sets to support continuous improvement of software applications and systems.
Identify hidden problems and patterns in data and use insights to improve coding hygiene and system architecture.
Collaborate with product, design, and backend teams to translate requirements into reliable, performant solutions.
Debug issues across UI and services; use basic SQL queries to validate data, investigate defects, and support root-cause analysis.
Ensure code quality through reviews, testing, documentation, and adherence to engineering standards.
Coach engineers on safe, compliant adoption of AI-assisted development practices and responsible AI use in engineering workflows.