Lead Software Engineer - Agentic AI

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As a Lead Software Engineer at JPMorgan

Chase within the Consumer and Community Banking - Deposits 2.0 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.

• 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.

• 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 Type Script / 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 scalable microservices using FastAPI, Spring Boot, or Node.js to expose agent interfaces (REST, Web Sockets, Server-Sent Events for streaming tokens and tool calls).
• Demonstrated experience leading effective use of approved AI-assisted software development tools (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security.
• Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching engineers on safe, compliant adoption within delivery practices
• Agentic Frameworks & Orchestration:
  Production experience with multi-agent and workflow orchestration frameworks (e.g., Lang Graph, Auto Gen,…