Java Lead Software Engineer

JPMorgan Chase & Co.; Greater London; On-site; GBP 90,000 - 140,000; Full time

Job summary

JPMorgan Chase & Co. in Greater London seeks a Lead Software Engineer to deliver trusted, market-leading technology within CIB - Markets Technology.

You will contribute as a core technical leader, delivering secure, scalable solutions across multiple business functions to support firm objectives. You will drive enterprise AI-assisted engineering practices, guide code review and testing strategies, and foster a culture of resilience and innovation.

Qualifications

• Advanced software engineering concepts and hands-on experience.
• Proven ability to deliver system design, development, testing and reliability.
• Experience using AI-assisted development tools to enhance quality and speed.

Responsibilities

• Execute creative software solutions, including design, development and debugging.
• Develop secure, high-quality production code and review others' code.
• Lead AI-assisted engineering practices to improve code quality and delivery speed.
• Use SDLC tools and AI-assisted capabilities to enhance automation and value.
• Identify and automate recurring issues to improve stability and resiliency.
• Lead evaluation sessions with vendors/teams on architecture and applicability.

Skills

Java

CI/CD

AI-assisted tooling

Secure coding

Leadership

Cloud-native

Education

Software engineering training

Job description

As a Lead Software Engineer at JPMorganChase within the CIB - Markets Technology, you are an integral part of an agile team that works to enhance, build, and deliver trusted, market-leading technology products in a secure, stable, and scalable way. As a core technical contributor, you are responsible for delivering critical technology solutions across multiple technical areas within various business functions in support of the firm's business objectives.

Job Responsibilities

• Execute creative software solutions, including design, development, and technical troubleshooting, with the ability to think beyond routine approaches to build solutions and break down complex technical problems.
• Develop secure, high-quality production code, and review and debug code written by others.
• Drive team adoption of enterprise-authorized AI-assisted engineering practices 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 (SDLC) toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation.
• Identify opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability and resiliency of software applications and systems.
• Lead evaluation sessions with external vendors, startups, and internal teams to drive outcomes-oriented probing of architectural designs, technical credentials, and applicability for use within existing systems and information architecture.
• Lead and contribute to communities of practice across Software Engineering; promote awareness and use of new and leading-edge technologies aligned to enterprise standards.
• Foster a team culture of diversity, opportunity, inclusion, and respect.

Required Qualifications, Capabilities, and Skills

• Formal training or certification on software engineering concepts and advanced applied experience.
• Hands-on practical experience delivering system design, application development, testing, and operational stability.
• Advanced proficiency in one or more programming languages (e.g., Java).
• Proficient in all aspects of the SDLC and advanced understanding of agile methodologies and practices, including CI/CD, Application Resiliency, and Security.
• Demonstrated experience leading effective use of approved AI-assisted software development tools (e.g., coding, code review, test acceleration, troubleshooting), including the ability to set team expectations for validating AI outputs for correctness, performance, and security.
• Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching engineers on safe, compliant adoption within delivery practices.
• In-depth knowledge of the financial services industry and its IT systems.
• Practical cloud-native experience at scale.

Preferred Qualifications, Capabilities, and Skills

• Experience with emerging technologies and architectural patterns.
• Strong communication and collaboration skills; ability to mentor and guide junior engineers.
• Familiarity with regulatory and compliance requirements in financial services.
• Experience working in global, cross-functional teams.
• Passion for continuous learning and professional development; ability to drive innovation and influence technology strategy.