Lead Software & Platform Engineer

LSEG•New York, NY

1d•$129,700 - $216,100•Hybrid

About The Position

We are looking for a hands-on Lead Software and Platform Engineer to drive the design, development, delivery, and operational reliability of large-scale, low-latency microservices-based trading platforms within our FX Engineering group. This role combines strong Java engineering expertise with platform ownership, production problem analysis, and DevOps/SRE practices. The successful candidate will remain close to the code while also providing technical leadership, guiding architecture decisions, improving platform reliability, and ensuring rapid diagnosis, patching, and release of business-critical services. You will work across engineering, architecture, infrastructure, and operations teams to build high-performance, resilient, observable, and scalable FX trading systems. The ideal candidate brings deep experience in Java, Spring Boot, microservices, Kubernetes, public cloud platforms, low-latency engineering, and production support of high-throughput distributed systems. We value engineers who take ownership, think critically under pressure, challenge assumptions, and deliver practical solutions that improve system performance, reliability, security, and developer experience.

Requirements

Strong hands-on expertise in Java development, with a passion for writing clean, efficient, maintainable, and production-grade code.
Proven experience developing enterprise applications using Spring Boot and microservices architecture.
Strong experience deploying, operating, and troubleshooting Java services on Kubernetes in a public cloud environment.
Experience building or supporting trading platforms, real-time systems, or other business-critical platforms requiring low latency and high throughput.
Proven experience operating as a technical lead or senior engineer influencing design, delivery, architecture, and engineering standards.
Strong understanding of distributed systems, system design principles, data structures, algorithms, and service-oriented architecture.
Expertise in concurrency, multithreading, JVM tuning, memory management, and performance optimization.
Strong knowledge of low-latency system design, high-throughput processing, profiling, benchmarking, and performance tuning.
Experience with production troubleshooting across application, Kubernetes, cloud infrastructure, networking, CI/CD, and observability layers.
Familiarity with network protocols and secure transport, including TCP, HTTP, WebSocket, and FIX, along with techniques for optimizing network communication.
Experience with DevOps practices, including automated testing, deployment automation, CI/CD pipelines, containerization, and infrastructure as code.
Ability to investigate and resolve complex, cross-system production issues using structured problem-solving and data-driven analysis.
Experience working in Agile engineering environments using modern software development practices.
Strong communication and stakeholder management skills, with the ability to explain complex technical issues clearly to both technical and non-technical audiences.
Ability to work effectively in a globally distributed team while balancing hands-on delivery, technical leadership, and production ownership.

Nice To Haves

Experience with public cloud platforms and cloud-native architecture, preferably Azure, AWS, or GCP.
Experience with Kubernetes ecosystem tools such as Helm, ingress controllers, service mesh, secrets management, and deployment strategies.
Experience with CI/CD tools such as GitLab CI/CD, GitHub Actions, Jenkins, or similar platforms.
Experience with infrastructure as code tools such as Terraform or equivalent technologies.
Experience with observability platforms such as DataDog, Grafana, Prometheus, ELK/OpenSearch, Splunk, BigPanda, or similar tools.
Knowledge of trading systems, FX markets, market data platforms, order execution flows, or financial-market infrastructure.
Experience mentoring engineers and improving engineering practices across teams.
Strong passion for technology, continuous learning, automation, and improving the reliability of mission-critical systems.
Experience using data-driven insights and AI-assisted tools to improve observability, automate operational workflows, accelerate incident diagnosis, generate tests, support code analysis, or improve developer productivity is highly valued. Curiosity, a learning mindset, and the practical application of AI-enabled engineering practices are most important.

Responsibilities

Lead the design, development, and delivery of large-scale, low-latency, high-throughput trading platform services within the FX Engineering group.
Build and maintain production-grade Java, Spring Boot, and microservices-based applications that support critical trading workflows.
Design, build, deploy, and operate Java services running on Kubernetes in public cloud environments such as Azure, AWS, or GCP.
Remain hands-on with the codebase while providing technical leadership across design, implementation, testing, release, and production support.
Perform deep technical analysis of complex production issues across application, platform, infrastructure, network, and deployment layers.
Identify issues in the platform and DevOps pipeline, propose effective solutions, and quickly patch, test, and release fixes to restore or improve platform stability.
Provide technical leadership and mentorship to engineers, fostering best practices in coding, performance engineering, system design, observability, and operational excellence.
Partner closely with architects, product teams, DevOps, infrastructure, and other engineering groups to define and deliver scalable solutions for FX trading.
Contribute to and guide the evolution of system architecture, ensuring performance, scalability, resilience, security, and maintainability.
Design, build, and support high-performance trading venues, platform services, and real-time data processing components.
Lead efforts to improve system observability, reliability, alerting, troubleshooting, and operational readiness.
Develop automation to detect, prevent, and resolve production issues, reducing manual effort, downtime, and latency impact.
Drive continuous improvements across performance optimization, cost efficiency, security, deployment quality, and developer experience.
Champion Agile, DevOps, and SRE practices, including CI/CD, automated testing, infrastructure as code, operational acceptance, and production readiness reviews.
Collaborate with global teams to investigate cross-system issues, perform root-cause analysis, and deliver long-term corrective actions.
Produce clear technical documentation, incident analysis, runbooks, troubleshooting guides, and knowledge-base articles.