Lead Software Engineer- Python / Quant Developer / Quant Research

<p>We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible.</p><p>As a Lead Software Engineer- Python / Quant Development / Quant Research at JPMorganChase within the Asset and Wealth Management Technology 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.</p><p>We are looking for developers to contribute to the transformation of the Quant Research Platform and Portfolio Construction and Management stack into an industry-leading platform. If you are an expert in Python, business-focused, and have a strong grounding in statistical methods and data analytics, please apply. You will work alongside Quant Research on model development, validation workflows, and the build-out of reusable Python Quant libraries that standardize research-to-production patterns and accelerate delivery across the platform. You’ll be required to apply your depth of knowledge and expertise across the software development lifecycle, partnering continuously with Quant Research on a daily basis.</p><h3>Job Responsibilities</h3><ul><li>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</li><li>Develops secure and high-quality production code, and reviews and debugs code written by others</li><li>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.</li><li>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.</li><li>Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems</li><li>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</li></ul><h3>Required qualifications, capabilities, and skills</h3><ul><li>Formal training or certification on software engineering concepts and 5+ years applied experience</li><li>Hands-on practical experience delivering system design, application development, testing, and operational stability</li><li>Strong experience with Python coding</li><li>Experience in financial Services across Asset Classes</li><li>Knowledge of statistical methods, quant or data analytics</li><li>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.</li><li>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</li><li>Proficient in all aspects of the Software Development Life Cycle</li><li>Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security</li><li>In-depth knowledge of the financial services industry and their IT systems</li><li>Practical cloud native experience</li></ul><h3>Preferred qualifications, capabilities, and skills</h3><ul><li>CFA charter holder</li><li>Experience with systematic portfolio management</li><li>Experience with model development, validation workflows, and the build-out of reusable Python Quant libraries</li></ul><br />#J-18808-Ljbffr