Lead Software Engineer - Full Stack Java/ React/ Cloud/ AI
The Lead Software Engineer will design, develop, and troubleshoot secure software solutions for wholesale credit risk systems while driving the adoption of AI-assisted engineering practices. The role involves leading technical teams, ensuring code quality, and integrating cloud-native technologies within a financial services environment.
- Compensation
- Not disclosed
- Location
- Houston, TX, United States
- Work setup
- Not specified
- Seniority
- Lead
- Employment
- Not specified
- Experience
- 5+ years
- Category
- Fullstack
- Posted
Skills
Must have
- 5+ years of applied software engineering experience
- Hands-on experience in system design, application development, testing, and operational stability
- Advanced proficiency in one or more programming languages
- Experience leading the use of AI-assisted software development tools
- Understanding of responsible AI use in engineering workflows
- Proficiency in all aspects of the Software Development Life Cycle
- Advanced understanding of agile methodologies, CI/CD, application resiliency, and security
- In-depth knowledge of the financial services industry and IT systems
- Practical cloud native experience
Nice to have
- Experience with data architecture and design
- Familiarity with modern front-end technologies
- Exposure to cloud technologies
- Experience building GraphQL and APIs
Full description
As a Lead Software Engineer at JPMorganChase within the Corporate Technology - Wholesale Credit Risk group, 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 core technical contributor, you are responsible for conducting critical technology solutions across multiple technical areas within various business functions in support of the firm’s business objectives.
Job responsibilities
- 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
- Develops secure and high-quality production code, and reviews and debugs code written by others
- 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.
- Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems
- Leads evaluation sessions with external vendors, startups, and internal teams to drive outcomes-oriented probing of architectural designs, technical credentials, and applicability for use 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 in one or more programming language(s)
- 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