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.