VP, Engineering Lead - Equities & Brokerage, Wealth Management Technology

About the role

The VP, Engineering Lead for Equities, Brokerage and Crypto drives the technical execution of multi-asset trading platforms in Singapore. The role calls for a hands-on, full-stack architect combining deep trading domain knowledge with expertise in React.js, Spring Boot, Java, automated testing, TDD and GenAI-native development. You will lead, scale and align cross-functional agile engineering teams distributed across Singapore and other global regions.

Key responsibilities

• Direct architectural strategy and code quality across React.js frontends, Spring Boot microservices and high-throughput Java trading backends.
• Pioneer the integration of Generative AI tools (e.g. Copilot, LLM agents) into the development lifecycle to accelerate engineering velocity and build AI-powered trading features.
• Lead, mentor and align distributed agile scrum teams across Singapore and other international regions, ensuring seamless cross-border delivery.
• Enforce strict automated testing cultures, including unit testing frameworks such as JUnit and Mockito, and end-to-end testing pipelines with Playwright.
• Oversee technical implementations for equities execution, retail brokerage services and secure crypto/digital asset integration.

Required profile

• 12+ years in software engineering, with 5+ years leading multi-region, distributed agile teams.
• Deep experience in FinTech, crypto, high-frequency trading or digital brokerage platforms; prior banking experience is highly beneficial but not mandatory.
• Expert-level Java developer with extensive experience building enterprise-grade, concurrent and secure services using Spring Boot.
• Proven track record implementing unit tests and automated E2E testing frameworks.
• Practical experience using GenAI tools for native development or embedding AI capabilities into financial or trading applications.

Required skills

• React.js, Spring Boot, Java
• JUnit, Mockito, Playwright
• WebSockets and real-time data streaming
• TDD and GenAI development practices