Software Engineer III - Java Full Stack

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 Asset and Wealth Management Technology team, 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
• Designs, builds, and operates microservices and APIs for Tax Platform capabilities using Java (primary) and Python (as needed), with strong engineering discipline across testing, code reviews, automation, and observability
• Builds and supports event-driven/data streaming solutions using Kafka (topic design, producers/consumers, schema management patterns, error handling/retries, idempotency, and operational monitoring)
• 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
• Develops and operates services on Private Cloud platforms, contributing to deployment automation, resiliency patterns, and platform reliability in production environments
• Proactively identifies hidden problems and patterns in data and uses these insights to drive improvements to coding hygiene, platform resiliency, and system architecture

• 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 modern programming languages and database querying languages
• Proficiency in Java and React, with experience building microservices-based applications; willingness to learn and adopt new technologies as needed
• Hands-on experience with Kafka processing/streaming (building and operating producers/consumers; understanding of delivery semantics, ordering, retries, and monitoring)
• Experience with Private Cloud and/or cloud platforms ,distributed systems, and web technologies including RESTful APIs, web services and JSON
• 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.
• Solid understanding of agile methodologies such as CI/CD, application resiliency, and security

• Working proficiency in Python
• Experience building platforms in regulated / controls-heavy environments requiring auditability and data governance
• Familiarity with LLM integration patterns (e.g., retrieval-augmented approaches, tool/function calling, prompt templates, evaluation frameworks)
• Familiarity with modern front-end technologies
• Exposure to cloud technologies