Lead Java Engineer: AI-Driven, Secure & Scalable

J.P. MORGAN; Bournemouth; On-site; GBP 90,000 - 150,000; Full time

Job summary

J.P. Morgan is seeking a Lead Software Engineer within Cash Asset Management to join an agile team delivering trusted, market-leading technology products.

You will contribute across design, development, testing, and operational stability while driving AI-assisted engineering practices to improve code quality and delivery speed. Candidates should have strong SDLC expertise and practical cloud-native experience.

Qualifications

• Formal training or certification in software engineering principles and practice.
• Hands-on experience delivering system design, development, testing, and operational stability.
• Advanced proficiency in one or more programming languages.
• Experience using enterprise AI-assisted development tools with secure outputs.
• Strong emphasis on responsible AI use in engineering workflows.
• Solid understanding of the Software Development Life Cycle and CI/CD practices.

Responsibilities

• Execute creative software solutions and tackle complex problems beyond routine approaches.
• Develop secure, high-quality production code; review and debug peers' work.
• Lead adoption of AI-assisted engineering practices to improve quality and speed.
• Apply SDLC tools and automation to increase value and efficiency.
• Identify recurring issues and drive automation for stability.
• Lead evaluation sessions with vendors and internal teams on architecture and design.

Skills

Software engineering fundamentals

System design

Programming languages

AI-assisted development tools

Responsible AI practices

Software Delivery Lifecycle

Education

Formal training in software engineering

Tools

CI/CD pipelines

Cloud native

Job description

J.P. Morgan is seeking a Lead Software Engineer within Cash Asset Management to join an agile team delivering trusted, market-leading technology products.

You will contribute across design, development, testing, and operational stability while driving AI-assisted engineering practices to improve code quality and delivery speed. Candidates should have strong SDLC expertise and practical cloud-native experience.