Build trusted, market-leading technology products that power JPMorganChase. In this role, you’ll be a core technical contributor on an agile team, delivering secure, stable, and scalable solutions. You’ll tackle complex problems across multiple technical areas, improve operational stability through automation, and help raise engineering standards across the organization. If you enjoy hands-on engineering work and influencing how teams build, run, and evolve software, this is an opportunity to grow your impact.
Job Summary:
As a Lead Software Engineer (Vice President) in our Technology organization, you will enhance, build, and deliver technology products in a secure, stable, and scalable way. You will conduct critical technology solutions across multiple technical areas and business functions to support the firm’s objectives. You will contribute hands-on through design, development, and troubleshooting, while also identifying opportunities to automate recurring issues and improve operational resilience. You will help evaluate emerging technologies and contribute to an inclusive, high-performing engineering culture.
Job Responsibilities
- Execute creative software solutions through design, development, and technical troubleshooting to break down complex problems
- Develop secure, high-quality production code and review and debug code written by others
- Identify opportunities to eliminate or automate remediation of recurring issues to improve operational stability of applications and systems
- Lead evaluation sessions with external vendors, startups, and internal teams to assess architectural designs, technical credentials, and fit within existing systems and information architecture
- Lead communities of practice across Software Engineering to drive awareness and adoption of new and leading-edge technologies
- Contribute to a team culture of diversity, equity, inclusion, and respect
- Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment 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 establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team
- 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 in software engineering concepts
- Hands-on experience delivering system design, application development, testing, and operational stability
- Advanced programming capability in Python
- Strong analytical and problem-solving skills
- Experience with object-oriented programming
- Proficiency in automation and continuous delivery methods
- Advanced understanding of agile methodologies, including continuous integration and delivery, application resiliency, and security practices
- Demonstrated proficiency in software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile)
- Practical cloud-native experience
- 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
- Knowledge of AWS data sources
- Experience with SecDB, Athena, or Quartz platforms
- Macro trading business knowledge
- UI experience with React.js and Node.js
- Experience building microservices and distributed computing solutions
- Knowledge of data modeling, performance engineering, and regression testing