Lead Software Engineer - Java/SpringBoot

JP Morgan Chase · Bournemouth, England ·

Last confirmed by our partners on 15 Oct 2026.

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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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