Agentic AI Full Stack Software Engineer III- Java/Python/React

As an Agentic AI Full Stack Software Engineer III- Java/Python/React at JPMorganChase within the Asset and Wealth Management Technology Team, you serve as a seasoned member of an agile team to design and deliver trusted market-leading technology products in a secure, stable, and scalable way.

You are responsible for carrying out critical technology solutions across multiple technical areas within various business functions in support of the firm's business objectives.

Job responsibilities


* Design, develop, test, and deploy external client-facing web applications that embed Generative AI and Agentic AI capabilities to enhance automation, personalization, and decision-making


* Build React-based UI experiences for LLM-powered workflows (e.g., chat, search, document Q&A, summarization, assisted advisory), emphasizing usability, accessibility, and performance


* Implement and integrate agentic AI workflows that support multi-step task execution, tool/API orchestration, and defined human-in-the-loop controls and guardrails


* Develop and maintain front-end architecture (component patterns, state management, routing, error boundaries) and collaborate on UX patterns for AI features (streaming responses, citations, traceability, retry/fallback flows)


* Implement Model Context Protocol (MCP) integrations to enable AI agents to securely connect to and interact with external data sources, APIs, and enterprise tools in real time


* Build and maintain scalable data pipelines and data processing workflows for both structured and unstructured data, leveraging cloud services to support LLM-based features and real-time client interactions


* Design and develop robust APIs and microservices to integrate AI/LLM models into client-facing platforms, ensuring seamless, low-latency experiences


* Leverage enterprise-authorized AI coding assist tools within the work environment to improve code quality, delivery speed, and productivity across complex deliverables (e.g., code generation/refactoring, unit test creation, documentation), while validating outputs through peer review, automated testing, and secure coding standards; contributes learnings and reusable patterns to improve broader team effectiveness


* Apply 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


* Implement observability, monitoring, and feedback loops for agentic AI systems to track agent behavior, detect hallucinations, and ensure reliability in high-stakes financial applications; Gather, analyze, synthesize, and develop visualizations and reporting from large, diverse datasets to inform product improvements, monitor model performance, and enhance client outcomes


* Partner closely with product, design, and business stakeholders to translate client needs and business requirements into scalable AI-dri...