Java Lead Software Engineer — Digital Markets Execution Technology, Execute

In this role you will lead the delivery of secure, scalable trading software within a cross‑functional agile team. You contribute technically across multiple domains to support firm objectives, shaping high‑performance, low‑latency systems. You’ll drive reliability, security, and observability while guiding API strategies and AI‑assisted engineering practices. The role combines hands‑on coding with architecture leadership to deliver trusted market‑leading technology.

• Execute end‑to‑end software solutions and set engineering standards for trading systems
• Design and build high‑performance, latency‑sensitive services with clear upstream/downstream dependencies
• Develop secure, production‑quality code and review others' work
• Lead technical analysis, planning, code reviews, architecture sessions, and retrospectives
• Establish reliability goals and implement observability, resilience patterns, and runbooks
• Lead incident response and post‑incident reviews to improve stability and automate remediation
• Uphold secure‑by‑default practices and risk/control standards across the SDLC
• Guide API/versioning strategies and deprecation paths for platform services
• Drive adoption of enterprise AI‑assisted engineering practices with validated outputs
• Mentor engineers and foster an inclusive, collaborative culture aligned to measurable outcomes

• Formal training or certification in software engineering concepts
• Hands‑on experience delivering design, development, testing, and operational stability for mission‑critical platforms
• Advanced in Java (17+), with strong concurrency and OO design
• Experience designing clean APIs and rollout strategies for distributed systems (integration and backward compatibility)
• Practical experience with Spring/Spring Boot, microservices, Kubernetes, Linux, and core networking/messaging concepts
• Proficiency across the Software Development Life Cycle (CI/CD, automated testing, resiliency, security)
• Experience using enterprise‑approved AI‑assisted development tools and setting team expectations for validating AI outputs
• Understanding of responsible AI in engineering workflows, data sensitivity, and secure inputs/outputs
• Effective communication with technical and non‑technical audiences in globally distributed teams

• Effective communication with technical and non‑technical audiences
• Mentoring and fostering a collaborative, inclusive culture
• Ability to drive continuous improvement and align with measurable outcomes
• Java (17+) with concurrency and memory management
• Spring/Spring Boot, microservices
• Kubernetes and Linux