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Fullstack Software Engineer III - Java
Job in
Glasgow, Glasgow City Area, G1, Scotland, UK
Listed on 2026-09-03
Listing for:
JP Morgan Chase
Full Time
position Listed on 2026-09-03
Job specializations:
-
Software Development
Software Engineer, Backend Developer, Java Developer, DevOps
Job Description & How to Apply Below
Chase, you'll collaborate with a diverse, agile team to deliver trusted, market-leading technology products. You'll have the opportunity to grow your career, work with cutting-edge tools, and help shape the future of digital document services. We value your expertise and encourage you to push the boundaries of what's possible. Join us and be part of a culture that celebrates innovation, inclusion, and continuous learning.
As a Software Engineer III at JPMorgan
Chase within the Digital Document Services team, you will design and deliver secure, stable, and scalable technology products that support the firm's core business objectives. You'll carry out critical technology solutions across multiple technical areas while working in a dynamic, agile environment. Your contributions will help drive meaningful improvements in software applications and systems, empowering you to collaborate, innovate, and make a lasting impact.
Job responsibilities
Execute software solutions across design, development, and technical troubleshooting to build innovative, production-ready applications
Create secure, high-quality production code and maintain algorithms that operate synchronously with appropriate systems
Produce architecture and design artifacts for complex applications, ensuring all design constraints and standards are met Gather, analyze, synthesize, and develop visualizations and reporting from large, diverse data sets to inform technical decisions
Identify hidden problems and patterns in data to drive improvements in coding hygiene and overall system architecture
Contribute to software engineering communities of practice and participate in events exploring new and emerging technologies
Foster a team culture of diversity, equity, inclusion, and respect through active collaboration and engagement
Leverages 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
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 proficient applied experience
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-scale environment using modern programming languages and database querying languages
Hands-on experience in server-side Core Java, XML, JSON, J2EE programming, Spring Framework, and associated design techniques
Experience developing web applications and REST APIs, with exposure to relational databases (Oracle/Sybase) or non-relational databases (MongoDB)
Working knowledge of version control using Git, continuous integration tools such as Jenkins, and automation testing tools such as Selenium, Cucumber, Flyway, or Concordion Knowledge of Linux, shell scripting, and application services including Apache, Tomcat, and Spring Boot
Experience with user interface technologies (Angular, Type Script, React) and user interface testing tools (Jasmine, Karma, Jest)
Working experience with cloud-native platforms (AWS, Kubernetes, or private cloud environments)
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…
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