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JPMorganChase is the largest bank in the United States by assets and one of the most systemically important financial institutions in the world, with a lineage running back through more than a thousand predecessor firms to the 1799 founding of the Bank of the Manhattan Company. It combines a dominant investment bank and markets business with Chase, the largest retail banking franchise in America, plus commercial banking and asset and wealth management. Headquartered in New York, the group is unusual among banks for the scale of its technology spending, running one of the largest engineering organisations of any financial institution and deploying its own internal AI platform across the firm.

As a Java Software Engineer II at JPMorgan Chase within the International Trust Services Technology Team, you are an integral part of an agile team that works to enhance, build and deliver trusted market-leading technology products in a secure, stable and scalable way.

Job responsibilities

  • Executes creative software solutions, design, development and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems
  • Write secure and high-quality code using Java and React, with limited guidance.
  • 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.
  • Design, develop and maintain cloud-native applications on AWS, considering upstream and downstream system impacts.
  • Apply knowledge of tools within the Software Development Life Cycle to improve automation and operational stability.
  • Gather, analyze and synthesize data from diverse sources to drive continuous improvement of software applications and systems.
  • Proactively identify and solve technical problems, contributing to system architecture and coding hygiene.
  • Collaborate with team members to foster a culture of diversity, opportunity, inclusion and respect.
  • Contribute to engineering communities of practice and events that explore new and emerging technologies.

Required qualifications, capabilities and skills

  • Formal training or certification on software engineering concepts applied advanced experience
  • Hands-on experience in system design, application development, testing and operational stability.
  • 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.
  • Advanced skills in Java with experience developing, debugging and maintaining code in a large corporate environment, with hands-on skills in Java 11+, Spring Boot and AWS
  • Intermediate-level familiarity with AWS or other cloud environment.
  • Strong coding fundamentals, including algorithms and data structures.
  • Experience across the Software Development Life Cycle and agile methodologies such as CI/CD, application resiliency and security.
  • Knowledge of software applications and technical processes within a technical discipline (e.g. cloud, artificial intelligence, platform engineering).
  • Experience with Transformative AI or LLM driven solutions.

Preferred qualifications, capabilities and skills

  • Hands-on practical experience in building agentic AI platforms for building AI-driven customer experiences
  • Knowledge of software application development and technical processes with considerable in-depth knowledge in one or more technical disciplines (cloud, artificial intelligence, machine learning, AI agents)
  • Experience applying expertise and new methods to determine solutions for complex technology problems in one or more technical disciplines
  • Practical cloud native experience
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