Lead Software Engineer - Backend Engineering - Java/Kotlin
Lead backend engineer on JP Morgan Chase's UK Chase digital bank Accelerator team, building secure, scalable, cloud-native customer products in Java/Kotlin on the JVM — covering domain modeling, zero-downtime releases, performance and reliability — while driving team adoption of AI-assisted engineering practices.
- Compensation
- Not disclosed
- Location
- LONDON, LONDON, United Kingdom
- Work setup
- Not specified
- Seniority
- Lead
- Employment
- Full time
- Experience
- Not specified
- Category
- Backend
- Posted
Skills
Must have
- Proficiency in JVM-based languages (Java/Kotlin)
- Formal training or certification on problem-solving concepts with proficient applied experience
- Demonstrated experience leading effective use of approved AI-assisted software development tools (coding, code review, test acceleration, troubleshooting), with ability to set team validation standard
- Strong understanding of responsible AI use in engineering workflows, including data sensitivity, secure handling of inputs/outputs, and coaching engineers on safe, compliant adoption
- Domain modeling techniques to build business products
- Structuring software so it is easy to understand, test and evolve
- Building scalable, resilient solutions avoiding single points of failure
- Developing secure code
- Zero-downtime releases and reliable, easy-to-operate systems
- Identifying and solving performance problems
- Adjusts quickly to changing priorities; learns and unlearns technologies quickly
- Long-term thinking — chooses technologies based on end goals
- Desire to teach others and share knowledge; team player, not hero developer
- High standards for personal and team performance
- Strong ethics; earns and maintains trust
Nice to have
- Multi-cloud experience
- Willingness to contribute outside their area of specialty
Full description
Out of the successful launch of Chase in 2021, we’re a new team, with a new mission. We’re creating products that solve real world problems and put customers at the center - all in an environment that nurtures skills and helps you realize your potential. Our team is key to our success. We’re people-first. We value collaboration, curiosity and commitment.
As a Lead Software Engineer at JPMorgan Chase within the Accelerator business, you are the heart of this venture, focused on getting smart ideas into the hands of our customers. You have a curious mindset, thrive in collaborative squads, and are passionate about new technology. By your nature, you are also solution-oriented, commercially savvy and have a head for fintech. You thrive in working 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.
While we’re looking for professional skills, culture is just as important to us. We understand that everyone's unique – and that diversity of thought, experience and background is what makes a good team, great. By bringing people with different points of view together, we can represent everyone and truly reflect the communities we serve. This way, there's scope for you to make a huge difference – on us as a company, and on our clients and business partners around the world.
Job responsibilities:
- Use domain modeling techniques to allow us to build best in class business products.
- Structure software so that it is easy to understand, test and evolve.
- Build solutions that avoid single points of failure, using scalable architectural patterns.
- Develop secure code so that our customers and ourselves are protected from malicious actors.
- Promptly investigate and fix issues and ensure they do not resurface in the future.
- Make sure our releases happen with zero downtime for our end-users.
- See that our data is written and read in a way that's optimized for our needs.
- Keep an eye on performance, making sure we use the right approach to identify and solve problems.
- Ensure our systems are reliable and easy to operate.
- Keep us up to date by continuously updating our technologies and patterns.
- Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment 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.