Lead Software Engineer - Java
JPMorgan Chase · GLASGOW, LANARKSHIRE, United Kingdom
About The Role
Are you ready to make a meaningful impact at one of the world's most innovative financial institutions? At JPMorganChase, we combine cutting-edge technology with a culture of collaboration and continuous learning — empowering you to grow your career while solving real-world challenges at scale.
As a Lead Software Engineer at JPMorganChase within the Reference Data Engineering team, you are a technical leader and a key contributor on an agile team, designing and delivering trusted market-leading technology products in a secure, stable, and scalable way. You are responsible for driving critical technology solutions across multiple technical areas within various business functions in support of the firm's business objectives. In this role, you will have the opportunity to deepen your technical expertise, mentor fellow engineers, and contribute to systems that power global financial markets.
Job responsibilities
- Lead the design and delivery of secure, high-quality software solutions, thinking beyond conventional approaches to solve complex technical problems at scale
- Create and maintain secure, high-quality production code and algorithms that run synchronously with appropriate systems
Produce architecture and design artifacts for complex applications while ensuring design constraints are met throughout the software development process
- Gather, analyze, synthesize, and develop visualizations and reporting from large, diverse data sets in service of continuous improvement of software applications and systems
- Proactively identify hidden problems and patterns in data and use these insights to drive improvements to coding hygiene and system architecture
- Write secure and high-quality code in Java, Angular, RESTful APIs, and SOAP, applying knowledge of tools within the Software Development Life Cycle toolchain to improve the value realized by automation
- Apply advanced technical troubleshooting to break down and resolve complex technical problems, applying system processes, methodologies, and skills for the development of secure, stable code and systems
- Mentor and guide junior engineers, fostering a culture of technical excellence, collaboration, and continuous improvement
- Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team
- 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
Required qualifications, capabilities, and skills
- Formal training or certification on software engineering concepts and advanced applied experience
- Hands-on practical experience in system design, application development, testing, and operational stability
- Proficiency in coding in one or more programming languages
- Experience developing, debugging, and maintaining code in a large corporate environment with one or more modern programming languages and database querying languages
- Strong understanding of the Software Development Life Cycle
- Experience writing well-tested, secure, and readable code in Java, UI frameworks such as Angular, RESTful APIs, and SOAP
- Experience with RESTful web service development using Spring Boot, Hibernate, or a similar framework
- 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
Preferred qualifications, capabilities, and skills
- Hands-on experience with cloud-native architectures and infrastructure
- Practical understanding of containerized application development and deployment using Docker, Kubernetes, Kafka, and AWS
- Experience with component-based web UI frameworks such as ReactJS, Angular, or Vue.js, and knowledge of relational databases and SQL, especially Oracle
- Experience working as part of an agile, user-centric product team
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