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This listing doesn't post a salary. Most similar roles pay
$159,875–$230,550.
Based on 240 similar postings.
Employer
About JPMorgan Chase
JPMorgan Chase & Co. is a global financial services firm and one of the largest banks in the world, offering investment banking, commercial banking, asset management, and consumer financial services.
JPMorgan Chase currently has
1226 open roles
on FindRole.
Listed pay typically runs
$156,750–$215,000
across 5 roles with salary data.
The Sr Lead Software Engineer - Agentic AI joins the Asset & Wealth Management Technology organization to develop production-grade solutions for Private Banking Web platforms. You will lead the full-stack design and delivery of secure, scalable applications, focusing on architecting agentic AI solutions that utilize large language models, orchestration frameworks, and workflow automation. Daily responsibilities include building microservices, integrating RESTful APIs, and managing cloud-native architectures while driving the adoption of AI-assisted engineering practices. You will utilize Python, Java, AWS, Docker, Kubernetes, and frameworks like LangGraph, Semantic Kernel, and CrewAI. The role involves solving complex business challenges by integrating AI-enabled capabilities for personalization and search, ensuring high-quality software through automated testing, CI/CD pipelines, and secure coding practices within a regulated financial services environment.
Lead full-stack design, development, and delivery of secure, scalable Private Banking Web applications.
Build production software using Python, Java, RESTful APIs, microservices, and event-driven architecture.
Architect agentic AI solutions leveraging LLMs, orchestration frameworks, tool calling, and enterprise data sources.
Integrate AI-enabled capabilities to enhance personalization, search, insights, and self-service for clients.
Drive adoption and governance of AI-assisted engineering practices to improve code quality and delivery speed.
Review designs and code to enforce secure coding practices and debug complex full-stack issues.
Develop reliable integrations using messaging, streaming, GraphQL, gRPC, and various database platforms.
Deliver engineering quality through automated testing, CI/CD pipelines, Infrastructure as Code, and containerization.
What we're looking for
Formal training or certification on software engineering concepts and 5+ years of applied experience.
Advanced hands-on full-stack software engineering expertise in designing and delivering production-grade enterprise applications.
Proficiency in Python, Java, modern web technologies, RESTful APIs, microservices, distributed systems, and data integration patterns.
Experience building secure multi-tier applications using AWS or other cloud platforms including compute, storage, networking, and deployment automation.
Deep knowledge of application security, authentication, authorization, data protection, secure SDLC practices, and financial services control expectations.
Experience developing agentic AI solutions using LLMs, prompt engineering, RAG, and frameworks like LangGraph, Semantic Kernel, or CrewAI.
Experience leading technical teams in a global agile environment and mentoring engineers across multiple disciplines.
Experience with Private Banking, Wealth Management, or regulated financial services technology (preferred).
Python
Agentic AI
LangGraph
CrewAI
AWS
Terraform
Generative AI
Retrieval-Augmented Generation
Vector Search
Distributed Systems
Site Reliability Engineering
infrastructure-as-code
Observability
Software Development Life Cycle