at J.P. Morgan
Bulge Bracket Investment BanksPosted 6 days ago
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**Lead Software Engineer - IP FS Data Protection & Recovery | Houston, TX** Drive innovative, secure solutions as a Lead Engineer.喊道 进行关键技术解决方案 across multiple domains, serving business needs and enhancing JPMorganChase's products.zösakes on key responsibilities including: creative problem-solving, coding with quality focus, adopting AI-assisted practices, improving operational stability, vendor evaluations, and collaboration across global technology teams. Bring 5+ years of hands-on experience, across full software development lifecycle, to lead a cross-functional team.czproficiency in Python, deployment tools, NoSQL databases like MongoDB, backend API using FAST API, agile methodologies (CI/CD, Resiliency, Security), and infrastructure technologies (Storage, Compute, Network) is essential. Survivability includes: leading AI-assisted tool integration, driving secure code practices, and coaching engineers on responsible AI use. Impact user experiences and save the day as a core technical contributor, thinking beyond conventional approaches.
- Compensation
- Not specified
- City
- Houston
- Country
- United States
Currency: Not specified
Full Job Description
Location: Houston, TX, United States
As a Lead Software Engineer at JPMorganChase within the Infrastructure Platforms Foundational Services Data Protection and Recovery Product Line, 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 firms 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
- Leads collaboration between technology teams to ensure global alignment.
- 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) - Python, Jules/Jenkins deployment
- 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
- Experience in Backend API using FAST API
- Advanced knowledge in databases as NoSQL (Mongo DB)
- Strong understanding of Infrastructure technologies - Storage, Compute and Network
