Lead Python Quant Engineer - AI-Driven Finance Platform

JPMorgan Chase & Co.; City of Rochester (NY); On-site; USD 170,000 - 210,000; Full time

Job summary

JPMorgan Chase & Co. in New York seeks a Lead Software Engineer to drive Python-based quant development and research within the Asset and Wealth Management Technology Team. You will contribute as a core technical contributor across the full software lifecycle.

You will collaborate with Quant Research on model development, validation workflows, and building reusable Python libraries that scale production research. Strong Python, statistics, and cloud-native experience are essential.

Qualifications

• Formal training or certification in software engineering with 5+ years of applied experience.
• Hands-on system design, development, testing, and operational stability experience.
• Strong experience with Python coding.
• Experience in financial services across Asset Classes.
• Knowledge of statistical methods, quant/data analytics.
• Proven use of AI-assisted development tools with built-in validation.

Responsibilities

• Executes innovative software solutions, designs, and debugging beyond routine approaches.
• Develops secure, high-quality production code and reviews peers' work.
• Leads AI-assisted engineering adoption and sets validation standards.
• Applies SDLC tools to improve automation and delivery value.
• Identifies and automates recurring issue remediation for stability.
• Leads evaluation sessions with vendors and teams on architecture feasibility.

Skills

Python coding

Statistical methods

Data analytics

Agile methodologies

AI-assisted development

Cloud native experience

Financial services knowledge

Leadership

Tools

CI/CD tools

AI-assisted development tools

Security tooling

Job description

JPMorgan Chase & Co. in New York seeks a Lead Software Engineer to drive Python-based quant development and research within the Asset and Wealth Management Technology Team. You will contribute as a core technical contributor across the full software lifecycle.

You will collaborate with Quant Research on model development, validation workflows, and building reusable Python libraries that scale production research. Strong Python, statistics, and cloud-native experience are essential.