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 with innovation 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.
Job responsibilities:
- Deliver end-to-end cutting-edge solutions in the form of cloud-native microservice architecture applications leveraging the latest technologies and the best industry practices.
- Design, estimate costs for and implement technical solutions written in Java/Kotlin
- Write unit, component, integration, end-to-end & performance tests
- Support the products you've built through their entire life cycle, including production and incident management
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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.
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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.
Required qualifications, capabilities and skills
- Formal training or certification on Java programming concepts and proficient advanced experience
- Recent hands-on professional experience as a back-end software engineer in an agile, dynamic and customer facing environment
- Recent experience with using a JVM language (Java/Scala/Kotlin, preferably Java 8+)
- Understanding of RESTful APIs and web technologies
- Understanding of relational databases
- Experience in all the stages of software development lifecycle (requirements, design, architecture, development, testing, deployment, release and support)
- Ability to work in a dynamic, agile environment within a diverse, inclusive and geographically distributed team
- Ability to focus on promptly addressing customer needs
- Technically curious, versatile and solution
- Excellent written and verbal communication skills in English
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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.
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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.
Preferred qualifications, capabilities and skills - Understanding of distributed systems and microservices architecture
- Understanding of cloud technologies (AWS, GCP, Azure, etc.)
- Understanding of messaging frameworks (Kafka, RabbitMQ, etc.)
- Experience in automating deployment, releases and testing in continuous integration, continuous delivery pipelines
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