Lead Software Engineer - Java/SpringBoot
JP Morgan Chase · Bournemouth, England ·
Last confirmed by our partners on 15 Oct 2026.
Overview
In this Lead Software Engineer role, you will design, implement, and troubleshoot secure, production-grade microservices in a fast-paced, cross-functional team within JPMorgan Chase’s Post-Trade Technology group. You’ll drive AI-assisted engineering practices to boost quality, delivery speed, and resilience across multiple business areas.
You’ll collaborate with vendors and internal teams to shape scalable, enterprise-grade solutions that support the firm’s market-leading technology objectives. This is an opportunity to influence architecture, security, and automation in a global financial services context.
Responsibilities
- Develop secure, high-quality production code and review peers’ work
- Lead adoption of enterprise AI-assisted engineering practices to improve code quality, delivery speed, and operational outcomes
- Apply SDLC tooling and automation to maximize value from automation
- Identify opportunities to automate recurring issues to improve stability
- Lead evaluation sessions with external vendors and internal teams on architectural designs and applicability
- Contribute to secure coding, automated testing, and validation standards
- Maintain awareness of enterprise resiliency and security expectations
- Support CI/CD, testing strategies, and application monitoring
Key requirements
- Formal training or certification in software engineering concepts
- Hands-on experience with system design, application development, testing, and operational stability
- Advanced Java programming
- Hands-on experience with Spring Boot, REST APIs, dependency injection, configuration, and actuator monitoring
- Proficiency in automation and continuous delivery methods
- Experience with relational databases (e.g., Oracle, Postgres) and/or NoSQL (e.g., MongoDB)
- Experience with AI-assisted software development tools and validating AI outputs for correctness, performance, and security
- Strong understanding of responsible AI use in engineering workflows and secure handling of data
- Proficiency across the Software Development Life Cycle
- Knowledge of agile methodologies (CI/CD, Pair Programming, TDD, Application Resiliency, Security)
- Familiarity with financial services IT systems
- Experience with cloud technologies (AWS) and data architectures (data lakes, data meshes)
- Ability to lead evaluations and drive outcomes-oriented decisions
- leadership
- collaboration
- communication
- Java
- Spring Boot
- REST APIs
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