Software Engineer III- Fullstack Java

As a Software Engineer III in Asset & Wealth Management – Data & Analytics at JPMorgan Chase, you will help build the instrument reference data platform that many teams rely on. You will write Java services that collect, enrich and share this data. We are now opening the platform to users in the US, EMEA and APAC, and building AI and automation tools for our engineers. If you enjoy hard problems in a growing cloud environment and want to shape what comes next, join us. Job Responsibilities Design and deliver core Java and Spring Boot services and APIs (REST and GraphQL), and the event (Kafka, MQ), streaming and bulk paths that distribute instrument data to consumers, owning each service from design through production stability Tackle complex technical problems and think beyond conventional approaches to build scalable, resilient solutions Find root causes of data and production issues by tracing instrument data across ingestion, enrichment, storage and downstream distribution, and fix the causes, not the symptom Develop, debug and maintain production code, business rules (Drools) and database changes in a large enterprise environment Uphold engineering excellence through thorough code reviews, automated and BDD testing, quality gates, and timely framework and security-vulnerability upgrades Produce architecture and design artifacts for complex applications and make sure design constraints are met in code Mentor engineers and contribute reusable patterns and tooling back to the group Build and improve automation and AI-based tooling that raises engineering leverage across the team Use enterprise-authorized AI coding-assist tools (code generation and refactoring, test creation, documentation) to improve quality, speed and productivity, validating outputs through peer review, automated testing and secure coding standards Work with engineering and product teams to deliver platform capabilities that support global investment operations at scale Required qualifications, capabilities, and skill Formal training or certification in software engineering concepts and advanced applied experience Strong hands-on experience with Java and Spring Boot (Java 17 or later), designing, developing, testing, debugging and maintaining production services in a large enterprise environment Experience distributing and consuming data using event and Kafka streaming, APIs (GraphQL and REST) and bulk methods and experience with relational (SQL) databases and at least one NoSQL store Hands-on experience in system design, application development, testing and operational stability, including production support Solid understanding of the Software Development Life Cycle, agile delivery, CI/CD, application resiliency and security with hands-on experience with enterprise-authorized AI-assisted development tools, and the ability to critically evaluate, validate and refine AI-generated output for correctness, performance and security Understanding of responsible AI use in engineering workflows (data sensitivity, secure handling of inputs and outputs, resiliency and security expectations), and the ability to guide peers on safe and effective use Preferred qualifications, capabilities, and skills Knowledge of data mesh distribution patterns using Snowflake and Starburst [CONFIRM: keep as preferred] Experience building on AWS services (compute, storage, messaging and access management), and experience with infrastructure as code such as Terraform Experience with a rules engine (for example Drools), Spring Batch, Liquibase and Cucumber (BDD) Knowledge of financial instrument reference data (identifiers such as ISIN, CUSIP and SEDOL, asset classes, security master concepts) Knowledge of Python Interest or experience in AI, agentic tooling or developer-automation platforms