Software Engineer III (Java/Agentic)

Design and deliver market-leading technology products in a secure and scalable way as a seasoned member of an agile team

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 the Auto Technology division, 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 are responsible for carrying out critical technology solutions across multiple technical areas within various business functions in support of the firm’s business objectives. Job responsibilities Executes software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or breakdown technical problems Develop modular components for agentic systems to enable intelligent automation and orchestration within business platforms; continuously build, test, and maintain these components. Own individual workstreams and Jira stories, consistently delivering high-quality code and features as part of broader AI/ML initiatives. Collaborate closely with team members to integrate agentic capabilities into existing systems and actively support solution delivery. Containerize and deploy agentic system components on cloud platforms (preferably AWS), strictly following established DevOps and infrastructure-as-code practices. Apply the latest advancements in agentic frameworks (such as LangGraph, Google ADK, AutoGen), LLMs, and GenAI to assigned tasks and features by staying up to date with industry developments. Document design decisions, implementation details, and results; clearly communicate progress and technical concepts to team members and stakeholders. Ensure code quality, security, and compliance by conducting thorough testing, peer reviews, and adhering to best practices. Leverages enterprise-authorized AI coding assist tools within the work environment to improve code quality, delivery speed, and productivity across complex deliverables (e.g., code generation/refactoring, unit test creation, documentation), while validating outputs through peer review, automated testing, and secure coding standards; contributes learnings and reusable patterns to improve broader team effectiveness. Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation. Required qualifications, capabilities, and skills Formal training or certification on software engineering concepts and 3+ years applied experience Hands-on experience developing and delivering agentic system components or autonomous AI features in production environments. Strong Python / JAVA programming skills, with a focus on modular, scalable, and maintainable code. Experience with cloud platforms (AWS), containerization (Docker), and infrastructure as code (Terraform). Familiarity with agentic frameworks (LangGraph, Google ADK, AutoGen) and integrating AI capabilities into business processes. Ability to work collaboratively in agile, cross-functional teams and deliver on assigned workstreams. Excellent problem-solving, communication, and documentation skills. Hands-on experience using enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, test creation, troubleshooting, or documentation) with demonstrated ability to critically evaluate, validate, and refine AI-generated outputs for correctness, performance, and security. Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; ability to guide peers on safe and effective usage within team practices. Preferred qualifications, capabilities, and skills Experience with Large Language Models (LLMs), GenAI, and retrieval-augmented generation (RAG). Exposure to agentic system design patterns, orchestration, and workflow automation. Ability to design and evaluate autonomous system features aligned with business goals.