Software Engineer III - Applied AI

We have an exciting and rewarding opportunity for you to take your software engineering career to the next level.

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

Job responsibilities

- Builds and delivers generative AI and agentic AI applications end to end, from prototype through production
- Develops agentic workflows, including tool-using agents and multi-agent collaboration
- Contributes to autonomous AI capabilities with appropriate guardrails, security controls, and responsible AI practices
- Implements orchestration and Retrieval-Augmented Generation (RAG) pipelines and integrates AI solutions with internal systems
- Builds and executes model and agent evaluations to measure and maintain solution quality
- Processes and analyzes large datasets that support AI solutions and applications
- Develops components for concurrent, multi-user, and real-time applications
- Creates secure, high-quality production code and deploys solutions on AWS using continuous integration and continuous delivery (CI/CD) practices
- Leverages enterprise-authorized AI-assisted development tools to improve code quality, delivery speed, testing, troubleshooting, and documentation while validating outputs for correctness, performance, and security
- Works closely with business users to gather feedback and rapidly iterate on solutions
- Contributes to engineering communities of practice and a team culture of diversity, opportunity, inclusion, and respect

Required qualifications, capabilities, and skills

- Formal training or certification on software engineering concepts and 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 demonstrated 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

Preferred qualifications, capabilities, and skills

- 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