Designs, develops, debugs, and maintains secure, scalable Java-based microservices on AWS. Produces architecture artifacts, leverages CI/CD and automation, analyzes large datasets for system improvements, and applies enterprise AI-assisted development and responsible AI practices (LLM orchestration, RAG, prompt engineering).
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 JPMorgan Chase within the Commercial & Investment Bank Payments Technology team, you will be an experienced member of an agile team, tasked with designing and delivering reliable, market-leading technology products that are secure, stable, and scalable.
Job responsibilities
As a Software Engineer III at JPMorgan Chase within the Commercial & Investment Bank Payments Technology team, you will be an experienced member of an agile team, tasked with designing and delivering reliable, market-leading technology products that are secure, stable, and scalable.
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
- Practical understanding of LLM orchestration, RAG, tool calling, prompt engineering, and dynamic reasoning
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
- Hands-on experience in JAVA, Spring, AWS, Terraform, Kafka/Streams, Oracle DB, Microservices-architecture
- Experience in developing, debugging, and maintaining code in a large corporate environment with one or more modern 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
- Familiarity with modern front-end technologies
- Exposure to cloud technologies
- Has experience Spring boot, Java, AWS experience
- Knowledge of API security best practices and SDK integration patterns
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