Lead Software Engineer - Java Full Stack

JPMorgan Chase & Co.; Greater London; On-site; GBP 120,000 - 180,000; Full time

Job summary

JPMorgan Chase & Co. in London seeks an experienced Software Engineering Leader to head the design, development and evolution of a critical risk analytics and reporting platform used by Risk managers and senior leadership across the firm.

You will partner with Product, Risk, Data, Architecture and Engineering teams to deliver secure, scalable technology solutions that improve risk oversight, decision making and operational efficiency, including adoption of AI-powered analytics and automation

Qualifications

• Formal training or certification in Software Engineering or Computer Science.
• Extensive hands-on experience with Java and modern application development frameworks.
• Experience building modern user interfaces using ReactJS and micro-frontends.
• Experience with high-volume data processing, analytics or reporting platforms.
• Proven experience delivering large-scale distributed applications in a complex enterprise environment.
• Strong knowledge of software architecture, design patterns, system integration and API development.
• 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.

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 and design systems.
• Define and govern UI architecture standards, design systems, extensibility frameworks, and frontend engineering best practices.
• Partner with Risk, Product and Data stakeholders to translate priorities into scalable technology solutions.
• Drive platform reliability, resiliency, observability 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 and workflow automation.
• Ensure solutions meet firm standards for security, controls, governance, resiliency and compliance.

Skills

Leadership

Stakeholder management

Communication

Architecture understanding

Education

Formal training in Software Engineering or Computer Science

Tools

Java

ReactJS

Micro-frontends

AWS

Containerization

APIs

Job description

Job Summary

We have an exciting and rewarding opportunity for an experienced Software Engineering Leader to join JPMorgan Chase.

As a Lead Software Engineer within Asset & Wealth Management Risk Technology, you will lead the design, development and evolution of a business-critical risk analytics and reporting platform used by Risk managers and senior leadership across the firm.

You will partner closely with Product, Risk, Data, Architecture, and Engineering teams to deliver secure, scalable and resilient technology solutions that enable better risk oversight, decision making and operational efficiency. In addition to driving delivery and technical excellence, you will help shape the adoption of AI-powered capabilities that enhance analytics, automation and user experience while maintaining strong governance and controls.

This role requires a combination of deep technical expertise, engineering leadership, stakeholder management and a passion for solving complex business and data challenges at scale.

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.