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# Lead Software Engineer - Python/PySpark/Databricks/AI

- **Company:** JPMorgan Chase & Co.
- **Location:** United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), Agile Methodology, Artificial Intelligence, Software Applications, Architectural Patterns, Automation of Tests, Software Quality, Code Review, Continuous Integration, Disaster Recovery, Revision Control Systems, Spring Framework, Python (Programming Language), Machine Learning, NoSQL, Software Tools, Secure Coding, Software Engineering, Software Systems, SQL Databases, Strategies of Testing, Toolchain, Istio, System Availability, Git, Pyspark, Kubernetes, Production Code, Bitbucket, Restful APIs, Domain Driven Design, Code Restructuring, Docker, Jenkins, Databricks, Microservices
- **Published:** July 9, 2026
- **Apply:** https://jpmc.fa.oraclecloud.com/hcmUI/CandidateExperience/en/sites/CX_1001/requisitions/preview/210758851

## 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
 * Excellent knowledge and experience in System Design, Domain Driven Design and Microservices
 * Experience leading in monolith to microservices journey of a 1000+ TPS, 24/7 platform
 * Experience with Architectural patterns for Scalability, High Availability, Performance & Disaster Recovery
 * Mandatory hands-on experience on core Java, Python, Spring and REST services
 * Experience with Kubernetes, Docker & Service mesh, SQL & NoSQL Databases, CI/CD tools like Jenkins, Version Control tools (BitBucket, Git), managing and tracking work using management tools like JIRA, and following and promoting Agile practices like TDD/BDD
 * Demonstrated proficiency in software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile, etc.)
 * 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

 * Modern emerging technologies

## Description

As a Lead Software Engineer - Python/Pyspark/Databricks/AI at JPMorganChase within the Consumer and Community Banking 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 break down technical problems

 * Develops secure high-quality production code, and reviews and debugs code written by others
 * 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 communities of practice across Software Engineering to drive awareness and use of new and leading-edge technologies
 * 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.


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