Lead Software Engineer - AI Platforms

GB Intelligence is transforming how Global Banking gets work done-bringing AI-driven insights and workflow automation into the heart of deal origination, market and sector intelligence, and client coverage.

As a Lead Software Engineer at JPMorganChase within the Commercial & Investment Banking - Global Banking Technology team, 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.

You will help deliver high-impact, production-grade capabilities: building scalable and resilient services, engineering secure data flows, and integrating seamlessly with the tools bankers rely on every day (CRM, market data platforms, modeling environments, and document/compliance systems).

You'll turn complex client, deal, and market data into trusted insights and outputs-then operationalize them across downstream systems to accelerate execution, strengthen risk discipline, and elevate the day-to-day experience for Global Banking teams.

Job responsibilities



* Design and implement complex software components across backend services, APIs, and UI experiences using Java, Python, and React, applying sound engineering judgment and pragmatic architecture.


* Build and refine agentic capabilities using the Smart SDK, including tool integration, orchestration patterns, and safety/reliability guardrails suitable for production use.


* Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team.


* Applies 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.


* Develop and optimize RAG pipelines end-to-end (ingestion, chunking, embeddings, retrieval, reranking, prompt/response patterns), improving relevance, latency, and robustness with OpenSearch and continuous measurement.


* Write secure, high-quality production code and raise the bar through code reviews, debugging, and hands-on mentorship-improving maintainability, performance, and consistency across the codebase.


* Drive operational excellence by identifying recurring issues and implementing automation, preventative controls, and reliability improvements to reduce toil and improve system stability.


* Engineer data and search solutions using Pos...