Lead Software Engineer, Securities Services Technology

J.P. Morgan’s Commercial & Investment Bank is a global leader across banking, markets, securities services and payments. Corporations, governments and institutions throughout the world entrust us with their business in more than 100 countries. The Commercial & Investment Bank provides strategic advice, raises capital, manages risk and extends liquidity in markets around the world. 

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