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Lead Software Engineer - AI Tooling
lead · Technology / Software Development
Join a collaborative technology team where your ideas help shape the tools and platforms that support employees across JPMorganChase. You will build reliable, scalable solutions, contribute to modern engineering practices, and help advance AI-enabled capabilities that make work simpler, faster, and more effective. This is an opportunity to grow your technical expertise while delivering meaningful impact in a secure and inclusive environment. As a core technical contributor, you will conduct critical technology solutions across multiple technical areas, supporting the firm’s business objectives. We value your creativity and encourage you to think beyond routine approaches to build innovative solutions.
Job Summary:
As a Lead Software Engineer – AI Tooling in Employee Platforms, you will design and deliver trusted technology products that are secure, stable, and scalable. You will work with us in an agile environment to create new features, improve AI tooling, and support cloud platform integration. Your work will help empower employees through innovative solutions that improve productivity, resilience, and user experience. You will be an integral part of an agile team, enhancing and building market-leading technology products. You will help drive outcomes-oriented probing of architectural designs and technical credentials.
Job Responsibilities:
- Design and deliver secure, high-quality software solutions that support employee-facing technology products
- Develop, debug, and maintain production code using modern engineering practices and scalable design patterns
- Contribute to architecture and design artifacts while ensuring software solutions meet functional, security, and resiliency requirements
- Build and enhance AI-enabled tooling, including solutions that support agentic workflows and improved developer productivity
- Analyze complex data sets and create insights, reporting, or visualizations that help improve applications and user outcomes
- Collaborate with product, design, engineering, and cloud platform teams to deliver solutions in an agile environment
- Apply continuous integration, continuous delivery, testing, and operational practices to improve software quality and reliability
- Participate in software engineering communities and contribute to a culture of learning, inclusion, and technical excellence
- 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
- Executes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or breakdown technical problems
Required Qualifications, Capabilities, and Skills:
- Formal training or certification on software engineering concepts and proficient applied experience
- Experience developing, debugging, and maintaining software in a large-scale technology environment
- Proficiency with Python and experience applying it to production software development
- Experience using AI coding assistants or AI-enabled engineering tools to improve development workflows
- Understanding of AI agents, agentic flows, and how they can be applied to software solutions
- Working knowledge of the software development life cycle, including design, build, test, deploy, and support activities
- Experience with agile delivery practices, continuous integration, continuous delivery, application resiliency, and secure coding
- Practical experience with cloud-native development, preferably using Amazon Web Services
- Experience with one or more database querying languages and working with data to support application development
- Demonstrated experience leading effective use of approved AI-assisted software development tools (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security.
- Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching engineers on safe, compliant adoption within delivery practices
Preferred Qualifications, Capabilities, and Skills:
- Familiarity with modern front-end technologies and user-centered application development
- Experience working with relational or non-relational databases
- Experience with Java, Kotlin, or Spring Boot
- Hands-on practical experience delivering system design, application development, testing, and operational stability
- Advanced in one or more programming language(s)
- Proficient in all aspects of the Software Development Life Cycle
- Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security