Java Lead Software Engineer — Digital Markets Execution Technology, Execute

Overview

In this role you will lead end-to-end software solutions for trading platforms, shaping high-performance services with secure, scalable design. You will collaborate across teams to ensure reliability, security, and operational readiness while guiding architecture and development practices. You’ll drive improvements through incident response, observability, and AI-assisted engineering, delivering trusted market-leading technology. This is an opportunity to influence critical systems within Digital Markets Execution Technology and mentor a collaborative, inclusive engineering culture.

Responsibilities

• Executes and oversees end-to-end software solutions, architecture, and debugging for trading systems
• Designs latency-sensitive services with awareness of upstream/downstream dependencies
• Develops secure, production-grade code and reviews peers code
• Leads technical analysis, planning, code reviews, and architecture sessions to drive delivery
• Sets reliability goals and implements observability, resilience, and operational readiness
• Leads incident response and post-incident reviews to improve stability and automation
• Upholds secure-by-default practices and risk/control standards across the SDLC
• Guides API/versioning strategies and deprecation paths for platform services
• Drives adoption of enterprise AI-assisted engineering tools with validated outputs
• Mentors engineers and promotes inclusive, collaborative culture

Key requirements

• Formal training or certification in software engineering concepts
• Hands-on experience delivering design, development, testing, and stability for mission-critical platforms
• Advanced proficiency in Java (17+), with concurrency and OO design
• Experience designing clean APIs for distributed systems with compatibility considerations
• Experience with Spring/Spring Boot, microservices, Kubernetes, Linux, and core networking/messaging
• Proficiency across the SDLC including CI/CD, automated testing, resiliency, and security
• Experience leading use of enterprise-approved AI-assisted development tools and setting validation standards
• Understanding of responsible AI use in engineering workflows, including data sensitivity and security
• Effective communication with global, distributed teams
• Strong communication with technical and non-technical audiences
• Mentorship and team leadership
• Collaboration in cross-functional, distributed environments
• Java (17+), concurrency, memory management, OO design
• Spring/Spring Boot, microservices
• Kubernetes, Linux, networking/messaging concepts

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