Java Software Engineer II

Push the limits of what’s possible with us as an experienced member of our Software Engineering team. As an Experienced Software Engineer at JPMorganChase within the Global Technology team, you serve as a member of an agile team to design and deliver trusted, market-leading technology products in a secure, stable, and scalable way. In this role, you will help build and evolve the Portfolio Management Fixed Income platform delivering portfolio management capabilities purpose-built for Fixed Income and supporting end-to-end portfolio construction and implementation workflows. These workflows include intraday portfolio exposure monitoring, order management, scenario-based what‑if analysis, order sizing, automated pre-trade compliance checks, and order submission, enabling portfolio managers and traders to make informed decisions, stay aligned with mandate guidelines, and execute efficiently across Fixed Income markets. You will join the backend engineering team building and maintaining JVM-based microservices that power portfolio analytics, reporting, and trade sizing across these workflows. You’ll work in a well-structured, multi-module codebase governed by clear conventions, designing and operating resilient services and REST APIs within a modern SDLC that emphasizes quality, security, and operational excellence. Experience with Kotlin is valued; the service is progressively adopting Kotlin, so a willingness to work across both Java and Kotlin is important. Job Responsibilities Participates in designing and developing scalable and resilient JVM microservices (Java and/or Kotlin) using the Spring Boot ecosystem to contribute to continual, iterative improvements for product teams Strong fundamentals with relational databases, including schema design, writing and tuning SQL, and managing schema changes via migrations (e.g., Liquibase) 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 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 2+ years applied experience Hands-on practical experience in system design, application development, testing, and operational stability in a production environment Proficient in coding in Java Experience developing, debugging, and maintaining code in a large corporate environment with modern programming languages and database querying languages (SQL) Strong fundamentals with relational databases, including schema design, writing and tuning SQL, and managing schema changes via migrations (e.g., Liquibase) 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. Overall knowledge of the Software Development Life Cycle, including code review, testing strategies, release practices, and operational support Understanding of agile methodologies and modern engineering practices such as CI/CD, application resiliency, and security Preferred qualifications, capabilities, and skills Experience working with Kotlin Familiarity with modern front-end technologies Working knowledge of cloud concepts and services (e.g., AWS fundamentals such as RDS, S3, CloudWatch, and container platforms such as EKS/Kubernetes) Exposure to event-driven architectures and messaging (e.g., Kafka) Experience with containerization and platform engineering patterns (Docker, Kubernetes/EKS) Domain experience in financial services, including familiarity with capital markets, trading workflows, and portfolio management concepts