Develop and maintain Java 21/Spring Boot microservices and React/TypeScript frontends. Manage Terraform infrastructure deployed to AWS ECS, produce secure production code, contribute to architecture, analyze data, and improve software quality through testing, automation, and authorized AI-assisted development. Collaborate within an agile team while supporting application resiliency, security, and continuous improvement.
We have an exciting and rewarding opportunity for you to take your software engineering career to the next level.
As Software Engineer III at JPMorganChase within Asset and Wealth Management Technology and Alternative Investments 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. The role may include building mobile features that give customers and clients greater control over how they bank with us, shaping how big data can accelerate our trading systems, driving the next wave of merchant payments innovation, and supporting the integration of private and public cloud platforms.
As Software Engineer III at JPMorganChase within Asset and Wealth Management Technology and Alternative Investments 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. The role may include building mobile features that give customers and clients greater control over how they bank with us, shaping how big data can accelerate our trading systems, driving the next wave of merchant payments innovation, and supporting the integration of private and public cloud platforms.
Job Responsibilities
- Designs, develops, debugs and maintains applications built Java 21/Spring Boot microservices handling, React/TypeScript frontends, Vite.
- Manages Terraform infrastructure configurations deploying to AWS ECS
- Creates secure and high-quality production code and maintains algorithms that run synchronously with appropriate systems
- Produces or contributes to architecture and design artifacts for applications while 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.
- Identifies hidden problems and patterns in data and uses these insights to drive improvements to coding hygiene and system architecture
- Contributes to software engineering communities of practice and events that explore new and emerging technologies
- Adds to team culture of diversity, opportunity, inclusion, and respect
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
- Proficient in coding in Java & React, JavaScript languages
- Experience in developing, debugging, and maintaining code in a large corporate environment with one or more modern programming languages and database querying languages
- Overall knowledge of the Software Development Life Cycle
- 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.
- Understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
- Knowledge of software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile, etc.)
Preferred qualifications, capabilities, and skills
- Experience with AWS Cloud
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