Sr Lead Software Engineer — Digital Markets Execution Technology, Execute

London Source: WhatJobs

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Overview

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.

Responsibilities

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

Key requirements

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