Senior Lead Software Engineer - Java - Asset Management Trading
Summary
Build and maintain core Java trading platforms for asset management, integrating Kafka/AMPS for real-time order execution and collaborating with traders to optimize workflows.
Job Description As a Senior Lead Software Engineer within Asset Management Trading Technology, you will help transform trading. You will design, build, and evolve industry-leading platforms that manage orders and execute trades across diverse asset classes. Working closely with Traders, you will support critical applications in production and engineer solutions that automate and optimize the order management lifecycle. You will be part of a team that values technical excellence, creative problem-solving, and rapid delivery, where your expertise will directly shape the future of trading technology. Job Responsibilities
- Support critical applications in production, interacting directly with users to resolve issues
- Design and engineer scalable, high-performance trading systems across multiple asset classes.
- Collaborate directly with Traders to deliver impactful solutions.
- Build and develop core Java applications for mission-critical trading platforms.
- Architect and implement next-generation messaging and streaming technologies such as Kafka and AMPS.
- Drive technical innovation and contribute creative ideas for platform advancement.
- Drive the adoption and scaling of GenAI practices within the software development workflow, bringing creative ideas on how to use AI tooling effectively and reliably.
- Lead code reviews and mentor team members to ensure engineering excellence.
- Participate in the full software development lifecycle from design through to production.
- Focus on continuous improvement and fast, iterative delivery.
- Deploy code to production daily with confidence.
- Add to team culture of diversity, opportunity, inclusion, and respect
- Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team.
- Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation.
- Bachelor's Degree in Computer Science or equivalent
- Formal Training and certification on software engineering and 5+ years of applied experience
- Proven hands-on experience designing and building end-to-end software systems.
- Strong knowledge of core Java and object-oriented design principles. Kotlin nice to have.
- Experience with messaging and streaming technologies e.g. Kafka
- Solid understanding of modern software architecture and design patterns.
- Demonstrated ability to work in a fast-paced environment.
- Commitment to building reliable, scalable, and maintainable systems.
- Ability to collaborate effectively with cross-functional teams including Traders and Quants.
- Passion for code quality, engineering excellence, and elegant solutions.
- Dedication to continuous improvement and rapid delivery.
- Strong problem-solving skills and creative thinking
- Demonstrated experience leading effective use of approved AI-assisted software development tools (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security.
- Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching engineers on safe, compliant adoption within delivery practices
- Experience in financial services or Trading technology.
- Knowledge of distributed systems and microservices architecture.
- Understanding of observability and telemetry principles.
- Interest in financial markets and trading workflows.
- Experience mentoring or leading technical teams.
- Exposure to low-latency or high-throughput systems.