Lead Software Engineer - Java Full Stack

Job Summary

Additional responsibilities

• Lead the technical strategy, architecture and roadmap for a large-scale risk analytics and reporting platform.
• Lead the evolution of the platform's front-end architecture, including micro-frontend strategies, domain-driven UI design, modular deployment patterns, and reusable user experience capabilities across multiple business domains.
• Define and govern UI architecture standards, design systems, extensibility frameworks, and frontend engineering best practices to enable scalable and consistent product development across teams.
• Partner directly with Risk, Product and Data stakeholders to understand business priorities and translate them into scalable technology solutions.
• Drive platform reliability, resiliency, observability and operational excellence, including root cause analysis and continuous improvement activities.
• Lead integration across multiple internal platforms, services and data sources.
• Evaluate and implement AI, machine learning and generative AI capabilities to improve analytics, user productivity, decision support and workflow automation.
• Ensure solutions meet firm standards for security, controls, governance, resiliency and compliance.

Required qualifications, capabilities and skills

• Formal training or certification in Software Engineering, Computer Science or a related discipline and extensive applied experience.
• Strong hands-on experience with Java and modern application development frameworks.
• Deep experience designing and building modern user interfaces using ReactJS or similar technologies, including micro-frontend architectures, component-based design systems, and scalable frontend engineering patterns.
• Experience working with high-volume data processing, analytics or reporting platforms.
• Proven experience designing and delivering large-scale distributed applications in a complex enterprise environment.
• Strong knowledge of software architecture, design patterns, system integration and API development.
• Strong practical experience with AWS, containerization technologies and cloud-native architectures.
• Experience with CI/CD, automated testing, application resiliency and operational excellence practices.
• Experience leading technical delivery across multiple teams and stakeholders.
• Excellent communication and stakeholder management skills.

Preferred qualifications

• Experience integrating large language models (LLMs), intelligent assistants or AI-driven workflow automation into business applications.
• Understanding of AI governance, model controls, explainability and responsible AI practices.
• Experience delivering analytics, decision-support or risk-management solutions powered by AI technologies.