Software Engineer III - Applied AI

JPMorganChase•Jersey City, NJ

About The Position

As a Software Engineer III at JPMorganChase within Consumer & Community Banking, you will serve as a seasoned member of an agile team, designing and delivering trusted, market-leading technology products in a secure, stable, and scalable way. You will build generative AI and agentic AI solutions, delivering production-ready capabilities that address complex business and technology challenges.

Requirements

Formal training or certification in software engineering concepts and at least 3 years of applied experience.
Strong Python programming skills and hands-on experience with generative AI and AI/machine learning frameworks.
Hands-on experience with agent frameworks such as LangGraph, Google Agent Development Kit (ADK), or similar technologies.
Practical experience with large language models (LLMs), prompt engineering, skill and tool development, and Retrieval-Augmented Generation (RAG).
Experience with model or large language model evaluation and benchmarking.
Experience working with large datasets.
Understanding of concurrent, multi-user, and real-time application design.
Experience with AWS or another major cloud platform.
Hands-on experience using enterprise-authorized AI-assisted software development tools, with the ability to critically evaluate and validate AI-generated outputs for correctness, performance, and security.
Understanding of responsible AI use in engineering workflows, including data sensitivity considerations and secure handling of inputs and outputs.
Solid understanding of the Software Development Life Cycle and agile practices such as CI/CD, Application Resiliency, and Security.

Nice To Haves

Exposure to small language models (SLMs), large reasoning models (LRMs), and model fine-tuning.
Hands-on experience with AI projects, hackathons, or personal development projects.
Familiarity with vector databases and streaming architectures.
Experience with modern front-end technologies used to build AI-enabled user experiences.

Responsibilities

Build and deliver generative AI and agentic AI applications end to end, from prototype through production.
Develop agentic workflows, including tool-using agents and multi-agent collaboration.
Contribute to autonomous AI capabilities with appropriate guardrails, security controls, and responsible AI practices.
Implement orchestration and Retrieval-Augmented Generation (RAG) pipelines and integrate AI solutions with internal systems.
Build and execute model and agent evaluations to measure and maintain solution quality.
Process and analyze large datasets that support AI solutions and applications.
Develop components for concurrent, multi-user, and real-time applications.
Create secure, high-quality production code and deploy solutions on AWS using continuous integration and continuous delivery (CI/CD) practices.
Use enterprise-authorized AI-assisted development tools to improve code quality, delivery speed, testing, troubleshooting, and documentation, while validating outputs for correctness, performance, and security.
Work closely with business users to gather feedback and rapidly iterate on solutions.
Contribute to engineering communities of practice and a team culture of diversity, opportunity, inclusion, and respect.