An application made for this job — a tailored resume and cover letter that speak straight to the posting.
JPMorgan Chase & Co. in the United Kingdom is seeking a back-end software engineer to build cloud-native microservices in Java/Kotlin, delivering robust banking features and scalable APIs for customers.
You will own the code across the lifecycle, collaborate in an agile, distributed team, and work with enterprise AI-assisted development tools to raise quality and velocity while ensuring security and reliability.
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.
Our Back-End Engineering team is at the heart of this venture, focused on getting a great banking experience into the hands of our customers. We're looking for people who have a curious mindset, thrive in a collaborative environment, 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 teams that focus on specific products and projects. Depending on your strengths and interests, you'll have the opportunity to move between them and work in projects including fraud prevention, Investments, identity services, money transfers, debit and credit card payments, core banking, insurance products, reward campaigns, call-centre supporting innovations and more.
Leverages enterprise-authorized AI coding assist tools within the work environment to improve code quality, delivery speed, and productivity across complex deliverables (e.g., code generation/refactoring, unit test creation, documentation), while validating outputs through peer review, automated testing, and secure coding standards; contributes learnings and reusable patterns to improve broader team effectiveness.
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.
#ICBCareers #ICBEngineering