Software Engineer III - Java

Join one of the world's most innovative financial institutions and help shape the future of real-time liquidity management. At JPMorganChase, you'll work on technology that matters — platforms that give senior executives instant visibility into the firm's cash, credit, and collateral positions across the globe. This is your opportunity to grow your engineering career while contributing to solutions that directly impact how one of the world's largest financial institutions manages risk. As a Software Engineer III at JPMorganChase within the Cash Account Platform team, you will be part of a global Agile engineering team based in Bournemouth, building and evolving a suite of applications that support firmwide intraday liquidity management. You will contribute to real-time dashboards, cash forecasting, and funding functions that serve senior executives and institutional clients. Your work will directly support the firm's strategic push toward cloud-native architecture and modern engineering practices. The Cash Account Platform is a firm-wide strategic initiative that provides real-time visibility into Cash, Credit, and Collateral balances at the Firmwide, Line of Business, and Institutional Client level. As part of the Bournemouth development team, you will collaborate with engineers across multiple global locations, contributing to a platform that is central to the firm's risk management, oversight, and reporting capabilities. Job responsibilities Execute software solutions across design, development, and technical troubleshooting, thinking beyond conventional approaches to solve complex engineering challenges Create secure, high-quality production code and maintain algorithms that operate synchronously with critical financial systems Gather, analyze, synthesize, and develop visualizations and reporting from large, diverse data sets to drive continuous improvement of software applications Proactively identify hidden problems and patterns in data, using insights to improve coding hygiene and system architecture Contribute to software engineering communities of practice and events that explore new and emerging technologies Leverage enterprise-authorized AI coding assist tools within the work environment to improve code quality, delivery speed, and productivity (e.g., code generation/refactoring, unit test creation, documentation), while validating outputs through peer review, automated testing, and secure coding standards Apply 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 Champion a team culture of diversity, opportunity, inclusion, and respect Required qualifications, capabilities, and skills Formal training or certification on software engineering concepts and proficient applied experience Hands-on practical experience in system design, application development, testing, and operational stability Proficiency in Java 8 and above, including strong working knowledge of the Java ecosystem Solid understanding of the Spring framework and its ecosystem Hands-on practical experience with relational database management systems Experience developing, debugging, and maintaining code in a large-scale environment using modern programming languages and database querying languages Demonstrated understanding of the Software Development Life Cycle and agile methodologies, including continuous integration and delivery, application resiliency, and security practices Demonstrated knowledge of software applications and technical processes within a technical discipline such as cloud, artificial intelligence, machine learning, or mobile Hands-on experience with Unix/Linux operating systems Hands-on experience using enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, testing, troubleshooting, or documentation) with demonstrated ability to critically evaluate and validate AI-generated outputs Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations Preferred qualifications, capabilities, and skills Familiarity with modern front-end technologies such as JavaScript and React Experience with DevOps practices including continuous integration and continuous deployment tools such as Jenkins and SonarQube Exposure to job scheduling tools such as Autosys or Control-M Exposure to cloud technologies and cloud-native development patterns Exposure to NoSQL databases