Lead Software Engineer - Agentic AI

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 the Consumer and Community Banking - Deposits 2.0 platform, 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


* Executes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or breakdown technical problems


* Define and drive the platform roadmap for agent-based capabilities, focusing on measurable outcomes, reliability, and usability


* Lead end-to-end delivery of core agent platform components, including software development kits, reference implementations, and integration patterns


* Partner with product, engineering, risk, and control stakeholders to align requirements, prioritize trade-offs, and unblock execution


* Establish quality, performance, and operational standards for agent workloads, including monitoring, testing, and incident readiness


* Translate experimentation into production by driving clear architecture decisions, scalable designs, and repeatable deployment practices


* Guide responsible development practices by embedding governance, privacy, and model risk considerations into platform design


* Communicate technical strategy and progress to senior stakeholders with clarity, data, and pragmatic recommendations


* 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.

Required qualifications, capabilities, and skills


* Formal training or certification on software engineering concepts and 5+ years applied experience


* Proficiency in Python (primary for agent orchestration and LLM tooling) and/or TypeScript / Java / Go for enterprise backend integration.


* Data & RAG Systems: Designing hybrid search pipelines (dense vector retrieval, BM25, rerankers) paired with vector databases like Pinecone, Milvus, Qdrant, or pgvector.


* Backend & API Design: Building ...