Lead Software Engineer – Java/SpringBoot

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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