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Lead Software Engineer - Java at JPMorgan Chase, Glasgow.
Drive high-performance, low-latency cloud payments platform—lead architecture, mentorship, and AI-assisted engineering.
Job description
Join one of the world's most innovative financial technology teams and make a direct impact on how money moves globally. As part of JPMorganChase's Payments technology organization, you will work at the intersection of engineering excellence and real-world financial impact — building systems that matter to millions of customers every day. We offer a collaborative, inclusive environment where your ideas are valued, your growth is actively supported, and your contributions shape the future of payments technology. This is your opportunity to work with cutting-edge cloud-native technologies alongside some of the brightest engineers in the industry, with access to the resources and scale that only a firm like JPMorganChase can offer.
As a Lead Software Engineer at JPMorganChase within the Payments technology team, you will design and deliver high-performance, low-latency solutions for a fully cloud-based payments platform. You will play a central role in driving engineering quality, mentoring peers, and contributing to the stability and scalability of systems that serve customers worldwide. Working in an agile environment, you will collaborate across technical disciplines to deliver trusted, resilient products that directly support the firm's strategic objectives and growth.
Job responsibilities
- Design and deliver secure, high-quality production code across a cloud-native payments platform, ensuring performance, reliability, and scalability at every stage of development
- Review and debug code written by peers, providing constructive technical feedback that raises the quality bar across the team
- Drive 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
- 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
- Lead architectural design reviews and technical evaluations with internal stakeholders to ensure alignment with engineering standards and long-term platform goals
- Champion communities of practice across software engineering to advance adoption of emerging and leading-edge technologies
- Collaborate across teams to identify opportunities for engineering improvement, driving innovation and operational stability across the payments platform
- Foster a team culture grounded in diversity, inclusion, and continuous learning
Required qualifications, capabilities, and skills
- Formal training or certification on software engineering concepts and advanced applied experience
- Practical experience delivering end-to-end system design, application development, testing, and operational stability in production environments
- Advanced proficiency in at least one object-oriented programming language, with strong command of Java
- 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
- Proficiency in automation and continuous delivery methods
- Proficient across all aspects of the Software Development Life Cycle
- Advanced understanding of agile methodologies, including continuous integration and delivery, application resiliency, and security practices
- Demonstrated knowledge of cloud-native development and practical experience building or operating cloud-based systems
Preferred qualifications, capabilities, and skills
- Experience with Java, Kafka, and SQL in the context of high-throughput, distributed systems
- Hands-on experience with AI-assisted coding tools and a working understanding of core artificial intelligence or machine learning concepts
- Demonstrated ability to take end-to-end ownership of complex technical deliverables, driving solutions from design through production
- Familiarity with financial services technology environments and large-scale IT systems
- Experience contributing to or leading engineering communities of practice or technical guilds