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Full timeTechnology

Lead Software Engineer, Securities Services Technology

JPMorgan Chase & Co.Sydney, Sydney🇦🇺AustraliaPosted 26 Jun 2026

Why this role stands out

This hybrid Lead Software Engineer role at JPMorgan Chase & Co. offers a thrilling adventure to push technological boundaries and drive critical solutions within Securities Services Technology, making it an ideal opportunity for mid-senior engineers who excel at creative problem-solving and technical leadership. You will thrive by developing secure, high-quality code, architecting complex applications, and leveraging cutting-edge AI-assisted engineering practices to deliver impactful market-leading products.

Quick overview

SeniorityMid Senior
Employment typeFull Time
Work modeHybrid
LocationSydney, Sydney, Australia
JavaAgileCI/CDSystem Design

Job description

We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible.

As a Lead Software Engineer at JPMorganChase within the Commercial & Investment Bank (CIB) - Securities Services Technology, Instructure Capture team, you are an integral part of an agile team that designs, enhances, builds, and delivers trusted market-leading technology products in a secure, stable, and scalable way. As a core technical contributor and team leader, you will drive critical technology solutions across multiple technical areas and business functions in support of the firm's objectives.

Job Responsibilities
  • 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.
  • 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.
  • Produces and maintains architecture and design artifacts for complex applications; ensures design constraints (security, resiliency, performance, scalability) are realized in implementation.
  • 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.
  • 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.
  • Identifies opportunities to eliminate recurring issues and/or automate remediation to improve the operational stability of software applications and systems.
  • Gathers, analyzes, and synthesizes insights from large, diverse datasets, developing visualizations and reporting in service of continuous improvement of applications and systems.
  • Proactively identifies hidden problems and patterns (including from data and operational signals) and uses insights to improve coding hygiene and system architecture.
  • Contributes to software engineering communities of practice and events that explore new and emerging technologies; mentors engineers and strengthens a culture of diversity, opportunity, inclusion, and respect.
  • Leads evaluation sessions with external vendors, startups, and internal teams to assess architectural designs, technical credentials, and applicability within existing systems and information architecture.
Required Qualifications, Capabilities, and Skills
  • Formal training or certification on software engineering concepts and 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.
Preferred Qualifications, Capabilities, and Skills
  • Familiarity with modern front-end technologies.
  • Exposure to cloud technologies

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