Sr Lead Software Engineer - Agentic AI
Salary not listed • Jersey City, NJ, United States • Full-time
Posted 7d ago
No salary is listed. Many US states require employers to post a pay range, so ask about pay early.
Job Location
Jersey City, NJ, United States
Tech Stack
Remote Work Policy
On-site
Employment Type
Full-time
Categories
AI Agent Engineer
About the job
As a Senior Lead Software Engineer for Agentic AI at JPMorgan Chase within the Asset & Wealth Management (AWM) Technology organization, you will be an integral part of an agile team enhancing, building, and delivering market-leading technology products. You will drive significant business impact by applying deep technical expertise to tackle diverse challenges across multiple technologies. This role focuses on leading the development of production-grade solutions that harness agentic AI, large language models, and automation to improve the experience for advisors and clients in Private Banking. You will collaborate with product, design, architecture, cybersecurity, and data teams to solve complex business challenges and accelerate delivery.
Responsibilities
- Lead full-stack design, development, and delivery of secure, scalable Private Banking Web applications across front-end, back-end, service, data, and cloud tiers.
- Build high-quality production software using Python, Java, modern web technologies, RESTful APIs, microservices, and event-driven architecture.
- Develop responsive and reliable web experiences integrating user interfaces, APIs, business services, data platforms, and enterprise systems.
- Drive adoption and governance of approved AI-assisted engineering practices to improve code quality, delivery speed, and operational outcomes.
- Architect agentic AI solutions leveraging LLMs, AI agents, orchestration frameworks, tool calling, workflow automation, and enterprise data sources.
- Integrate AI-enabled capabilities to enhance personalization, search, insights, recommendations, and self-service across Private Banking Web experiences.
- Drive technical decisions across application architecture, cloud services, security controls, performance, observability, reliability, and production readiness.
- Review designs and code, debug complex full-stack issues, strengthen code quality, and enforce secure coding practices.
- Collaborate with product, design, data, architecture, cybersecurity, risk, and business stakeholders to deliver solutions aligned to enterprise standards.
- Mentor engineers, influence technical direction, and promote effective use of AI-assisted development tools, reusable skills, and engineering accelerators.
Requirements
- Formal training or certification on software engineering concepts and 5+ years of applied experience.
- Demonstrate advanced hands-on full-stack software engineering expertise with a proven track record of designing and delivering production-grade enterprise applications.
- Strong hands-on development experience with 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, identity, security, observability, and deployment automation services.
- Ability to apply deep knowledge of application security, authentication, authorization, data protection, secure SDLC practices, vulnerability remediation, and financial services control expectations.
- Demonstrated experience leading effective use of enterprise-authorized AI-assisted software development tools within the work environment.
- 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.
- Develop agentic AI solutions using LLMs, prompt engineering, retrieval-augmented generation, AI agents, tool calling, workflow orchestration, and frameworks such as LangGraph, Semantic Kernel, MCP, A2A, CrewAI.
- Design reliable integrations using messaging, streaming, GraphQL, gRPC, WebSocket, relational databases, NoSQL platforms, caching, search, and event-driven technologies.
- Deliver engineering quality through automated testing, CI/CD pipelines, Infrastructure as Code (IaC), containerization, Docker, Kubernetes, monitoring, logging, and production support.
- Lead technical teams in a global agile environment, influence architecture decisions, communicate with senior stakeholders, and mentor engineers across multiple disciplines.