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J.P. Morgan Personal Investing in the UK is seeking a Manager of Software Engineering to lead a squad of engineers within the Invest Tribe. You will shape technical direction, review architectures and deliver customer-focused initiatives with measurable impact.
You will mentor engineers, collaborate with product managers, drive AI-assisted practices, and ensure secure, scalable solutions across the SDLC. This role requires strong leadership, JVM expertise and a track record of delivering fintech
Behind every investment is a person with ambitions, motivations and values. While we know that every client is unique, they come to J.P. Morgan Personal Investing for the same reason: our straightforward and transparent approach to investing, and the trust that 150 years of J.P. Morgan heritage brings.
J.P. Morgan Personal Investing offers award-winning investments, products and digital wealth management services to over 275,000 investors in the UK. We built the business withinnovation as a core part of our ethos to give consumers the confidence and clarity to make informed investment decisions and achieve their financial goals.
As a Manager of Software Engineering at JPMorgan Personal Investing, you will be a credible engineering leader, in charge of a squad of engineers, technically savvy to influence your squad’s technical implementations and confident enough to challenge architecture decisions as you maintain focus on delivering initiatives and demonstrating customer value every step of the way.
Our Invest team is at the heart of this venture, focused on getting smart ideas into the hands of our customers. We're looking for people who have a curious mindset, thrive in collaborative squads, and are passionate about new technology. By their nature, our people are also solution-oriented, commercially savvy and have a head for fintech. We work in tribes and squads that focus on specific products and projects – and depending on your strengths and interests, you'll have the opportunity to move between them.
Job responsibilities:
Drives adoption and governance of approved AI-assisted engineering practices across teams to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test acceleration, release readiness, incident/root-cause analysis), while establishing measurable validation standards (secure coding, peer review, automated testing) and promoting reuse of proven patterns and automation within the SDLC/TLM toolchain.
Applies knowledge of tools within the Software Development Life Cycle toolchain, including approved AI-assisted development and automation capabilities, to improve the value realized by automation at scale.
Required qualifications, capabilities and skills:
Demonstrated experience leading effective use of enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, code review, test acceleration, troubleshooting) with 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 senior engineers/leads on compliant usage patterns and controls.
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