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# Lead Software Engineer - Java/Python/Databricks/AWS

- **Company:** JPMorgan Chase & Co.
- **Location:** Houston, TX, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), Agile Methodology, Artificial Intelligence, Amazon Web Services, Data Analysis, Software Applications, Automation of Tests, Cloud Computing, Software Quality, Code Review, Continuous Integration, Data Integration, Software Design Patterns, Python (Programming Language), Software Tools, Secure Coding, Software Engineering, Software Systems, Strategies of Testing, Toolchain, Enterprise Data Management, Data Ingestion, Information Technology, Production Code, Data Analytics, Data Management, Code Restructuring, Software Version Control, Databricks, Programming Languages
- **Published:** September 5, 2026
- **Apply:** https://www.houstonjobsite.com/job.asp?id=3375491682&tx=JT9789TTT&pt=1&aff=0B19D771-A501-4A5E-8338-2A822B784D54&utm_source=Job%20Feed&utm_medium=textkernel&utm_campaign=DE&utm_term=0B19D771-A501-4A5E-8338-2A822B784D54

## About the Role

* 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) (i.e., Python, Java, Databricks, AWS, etc.)
 * Experience in delivering system design (design patterns, reliability and scaling), application development, testing and support
 * 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 stakeholder management and communication skills with e xcellent analytical skills (i.e. problem solving)
 * 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
 * Experience dealing with growing data ingestion, data management and data analytics
 * Disciplined approach to code management, testing and deployment practices and being a self-starter with the ability to quickly pick up new ideas, concepts and technologies
 * Proficient in all aspects of the Software Development Life Cycle and in-depth knowledge of the financial services industry and their IT systems
 * Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security also experience

Preferred qualifications, capabilities, and skills

 * Certifications of any specific specialty (i.e., AWS Certified Cloud Practitioner, AWS Certified Data Engineer - Associate, etc.)
 * Experience with Data Integration and Analytical skills

## Description

As a Lead Software Engineer at JPMorganChase within the Corporate Sector - Corporate Data and Analytics Service team, 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., * 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


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