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$192,050–$242,850.
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
1117 open roles
on FindRole.
Listed pay typically runs
$186,160–$215,000
across 7 roles with salary data.
Sr Lead Software Engineer - Agentic AI joins the Asset & Wealth Management Technology team to develop production-grade solutions for Private Banking Web platforms. This role involves leading the full-stack design and delivery of secure, scalable applications across front-end, back-end, service, data, and cloud tiers. You will architect agentic AI solutions utilizing large language models, orchestration frameworks like LangGraph or CrewAI, prompt engineering, and retrieval-augmented generation to enhance personalization and search. Daily responsibilities include building microservices with Python and Java, managing RESTful APIs, and integrating event-driven architectures. You will also drive the adoption of AI-assisted engineering practices and manage infrastructure using Docker, Kubernetes, and CI/CD pipelines. The role focuses on solving complex business challenges in the private banking domain by integrating AI-enabled capabilities into web experiences while ensuring high standards for security, performance, and reliability.
Lead the full-stack design, development, and delivery of secure, scalable Private Banking Web applications.
Build production-grade software using Python, Java, microservices, RESTful APIs, and event-driven architectures.
Architect agentic AI solutions utilizing LLMs, orchestration frameworks, tool calling, and enterprise data sources.
Integrate AI-enabled capabilities to enhance personalization, search, and recommendations across digital platforms.
Drive the adoption of AI-assisted engineering practices to improve code quality, testing, and delivery speed.
Manage technical decisions regarding cloud services, security controls, performance, and production readiness.
Review designs and code while enforcing secure coding practices across globally distributed teams.
Mentor engineers and influence technical direction regarding AI tools and engineering accelerators.
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, and financial services control expectations.
Experience developing agentic AI solutions using LLMs, prompt engineering, RAG, orchestration frameworks (e.g., LangGraph, CrewAI), and tool calling.
Ability to lead technical teams in a global agile environment while mentoring engineers and influencing architecture decisions.
Experience with Private Banking, Wealth Management, or regulated financial services technology (preferred).