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Software Engineer III; Java​/Agentic)

Job in New York, New York County, New York, 10261, USA
Listing for: JPMorgan Chase & Co.
Full Time position
Listed on 2026-10-18
Job specializations:
  • Software Development
    AI Engineer (Applied/Software), Backend Developer, DevOps
Salary/Wage Range or Industry Benchmark: 120000 - 150000 USD Yearly USD 120000.00 150000.00 YEAR
Job Description & How to Apply Below

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 JPMorgan

Chase 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 work streams 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.
  • Containerizeand deploy agentic system components on cloud platforms (preferably AWS), strictly following established Dev Ops and infrastructure-as-code practices.
  • Applythe latest advancements in agentic frameworks (such as Lang Graph, Google ADK, Auto Gen), 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.
  • Ensurecode 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 (Lang Graph, Google ADK, Auto Gen) and integrating AI capabilities into business processes.
  • Ability to work collaboratively in agile, cross‑functional teams and deliver on assigned work streams.
  • 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.
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