Lead Software Engineer, Securities Services Technology

JPMorgan Chase JPMorgan Chase · Banking · Sydney, NSW, Australia · Commercial & Investment Bank

Lead Software Engineer for Securities Services Technology at JPMorgan Chase, focusing on designing, enhancing, building, and delivering market-leading technology products. The role involves driving critical technology solutions, executing software solutions, developing high-quality production code, producing architecture and design artifacts, and leading team adoption of AI-assisted engineering practices to improve code quality, delivery speed, and operational outcomes. The engineer will also apply knowledge of the SDLC toolchain, identify opportunities for automation, analyze datasets, and contribute to communities of practice. Requires formal training/certification, 5+ years of experience, proficiency in programming languages (e.g., Java/J2EE), SDLC/agile methodologies, AI-assisted tool usage, responsible AI principles, cloud-native experience, and financial services industry knowledge.

What you'd actually do

  1. Executes creative software solutions, including design, development, and technical troubleshooting, with the ability to think beyond routine approaches to build solutions and break down complex technical problems.
  2. Develops secure, high-quality production code and maintains algorithms and services that operate reliably with dependent systems; reviews, debugs, and improves code written by others.
  3. Produces and maintains architecture and design artifacts for complex applications; ensures design constraints (security, resiliency, performance, scalability) are realized in implementation.
  4. Drives team adoption of enterprise-authorized AI-assisted engineering practices to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), while setting consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns.
  5. Applies strong knowledge of the SDLC toolchain (CI/CD, automation, quality, observability), including enterprise-authorized AI-assisted development and automation capabilities, to increase the value realized from automation.

Skills

Required

  • Formal training or certification on software engineering concepts
  • 5+ years applied experience
  • Hands-on practical experience delivering system design, application development, testing, and operational stability.
  • Advanced proficiency in one or more programming languages, with strong practical experience in a large corporate environment (e.g., Java / J2EE and related ecosystem); experience with database querying languages.
  • Proficient in all aspects of the Software Development Life Cycle and strong understanding of agile methodologies, including CI/CD, application resiliency, and security.
  • Demonstrated experience leading effective use of approved AI-assisted software development tools (coding, code review, test acceleration, troubleshooting) and setting team expectations for validating AI outputs for correctness, performance, and security.
  • Strong understanding of responsible AI use in engineering workflows (data sensitivity, secure handling of inputs/outputs, adherence to resiliency and security expectations); experience coaching engineers on safe, compliant adoption.
  • Demonstrated knowledge of software applications and technical processes within at least one technical discipline (e.g., cloud, AI/ML, mobile, etc.).
  • Practical cloud-native experience.
  • In-depth knowledge of the financial services industry and IT systems.

Nice to have

  • Familiarity with modern front-end technologies.
  • Exposure to cloud technologies

What the JD emphasized

  • AI-assisted engineering practices
  • AI-assisted code review/refactoring
  • AI-assisted development and automation capabilities
  • responsible AI use in engineering workflows
  • approved AI-assisted software development tools