Lead Software Engineer
JPMorgan Chase · Plano, United States · 22d ago
Staff / Lead / PrincipalOn-siteSoftware Engineering
Our Consumer & Community Banking division serves our Chase customers through a range of financial services, including personal banking, credit cards, mortgages, auto financing, investment advice, small business loans and payment processing. We’re proud to lead the U.S. in credit card sales and deposit growth and have the most-used digital solutions – all while ranking first in customer satisfaction.
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 JPMorgan Chase within the Consumer & Community Banking - Digital Mobile org, you are an integral part of an agile team that works to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way.
As a Lead Software Engineer at JPMorgan Chase within the Consumer & Community Banking - Digital Mobile org, you are an integral part of an agile team that works to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way.
JOB RESPONSIBILITIES
- 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.
- 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
- Designs, builds, and maintains reusable CI/CD pipeline components (Jenkins Shared Libraries in Groovy and supporting Python tooling) that power mobile app and framework builds end to end, improving build reliability and reducing cycle time for the mobile engineering community.
- Develops and evolves Python/Django REST services and an emerging async FastAPI data platform (MongoDB-backed) that capture pipeline activity and stream real-time build and release insights to developers.
- Builds and hardens AI-assisted developer experiences (e.g., automated build-error analysis and fix suggestions) delivered through an LLM gateway that proxies Claude (Anthropic) via AWS Bedrock behind an OpenAI-compatible API.
- Applies agentic AI fundamentals, including MCP and ACP integrations, to deliver well-documented, developer-facing features quickly and responsibly.
- Partners with mobile app teams across iOS, Android, and cross-platform stacks to model build and release data and deliver responsive dashboards and developer tooling.
REQUIRED QUALIFICATIONS, CAPABILITIES, AND SKILLS
- Formal training or certification on software engineering concepts and 5+ years applied experience (NAMR/APAC - India/ LATAM/ Hong Kong)
- Formal training or certification on software engineering concepts and advanced applied experience (EMEA/LATAM-Brazil)
- Singapore follow local country guidance
- 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
- 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
- Proficient in all aspects of the Software Development Life Cycle
- Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
- Practical cloud native experience
PREFERRED QUALIFICATIONS, CAPABILITIES, AND SKILLS
- Proficiency in Python, including Django and/or FastAPI, for building backend services and developer tooling
- Hands-on experience with CI/CD and developer productivity tooling (Jenkins/Groovy a plus)
- Mobile build experience (iOS/Android, Fastlane, Gradle, Xcode)
- Experience with MongoDB or other NoSQL data modeling
- Hands-on experience with LLM APIs, prompt design, or AI developer tooling
- Familiarity with AWS (ECS, Bedrock), Docker, or streaming/event-driven architectures (e.g., Server-Sent Events)
- Swift/SwiftUI development experience