We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible.

As a Lead Software Engineer at JPMorganChase within Asset & Wealth Management, you are an integral part of an agile team that works to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. As a core technical contributor, you are responsible for conducting critical technology solutions across multiple technical areas within various business functions in support of the firm’s business objectives.

Job responsibilities:

• Design and deliver features across the full stack — backend APIs, AI agent orchestration, and frontend UI
• Build and maintain LLM tool integrations, keeping service responsibilities clean and well-bounded
• Integrate with internal and third-party financial data services, translating domain data into LLM-usable context
• Review the architectural surface of every feature before it ships
• Collaborate closely with team members — participating in design discussions, sharing context, and communicating trade-offs clearly both in writing and in conversation
• Keep documentation and inline comments current — stale docs are treated as bugs
• Adds to team culture of diversity, opportunity, inclusion, and respect

Required qualifications, capabilities, and skills:

• Formal training or certification on software engineering concepts and 5+ years applied experience
• Java + Spring Boot — REST APIs, clean service boundaries, modern Java idioms
• Strong architecture instincts — ability to reason about service boundaries, separation of concerns, layering, and long-term maintainability
• TypeScript + React — strict TypeScript, state management, real component design
• AI/LLM integration — hands-on experience with agentic systems: tool calling, structured output, context management, prompt design
• Distributed systems fundamentals — WebSocket, SSE, REST; able to debug across multiple services
• Clear communicator — comfortable discussing technical decisions with teammates, asking the right questions, and aligning on approach before diving into implementation

• Background in financial services, fintech, or wealth management — familiarity with investment products, portfolio concepts, or client data workflows is a plus
• Familiarity with MCP (Model Context Protocol) or similar LLM tool-integration patterns
• Experience with LangGraph or other graph-based agent frameworks (LangChain, AutoGen) is a plus
• Comfort operating at prototype pace — patterns still crystallizing, right abstraction not always obvious, expected to ask before guessing
• You'll join a small, high-ownership team building a next-generation AI-powered advisory platform that helps financial professionals work faster and smarter.
• This is full-stack, end-to-end work across a modern polyglot architecture: Java microservices, a Python AI agent, and a React frontend.