Lead Software Engineer, Python Software Engineer

JPMorgan Chase

Confirmed live yesterday Trusted

Quick summary

Work type: On-site
Location: Columbus, OH
Employment: Full-time
Posted: 13 days ago
Freshness: Confirmed live yesterday
Nearby: 99+ roles within 25 mi

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Salary context

How this pay compares to similar roles

Similar $176k

$129k $242k

below market most similar roles pay here above market

This listing doesn't post a salary. Most similar roles pay $142,400–$208,800.

Based on 240 similar postings.

Employer

About JPMorgan Chase

JPMorgan Chase & Co. is a global financial services firm and one of the largest banks in the world, offering investment banking, commercial banking, asset management, and consumer financial services.

JPMorgan Chase currently has 1226 open roles on FindRole.

Listed pay typically runs $156,750–$215,000 across 5 roles with salary data.

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At a glance

TL;DR · Lead Software Engineer, Python Software Engineer

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As a Lead Software Engineer – Python Software Engineer within the Chief Technology Office, you will join an agile team focused on delivering secure, stable, and scalable market-leading technology products. You will serve as a core technical contributor, designing and developing high-quality production code while troubleshooting complex technical problems across various business functions. Your daily work involves building AI-native components, automating remediation of recurring issues, and driving the adoption of enterprise-authorized AI-assisted engineering practices for code review and testing. You must possess advanced Python skills, practical cloud-native experience, and proficiency in automation, CI/CD, and the full Software Development Life Cycle. You will also lead communities of practice to promote shared frameworks and leading-edge technologies while ensuring responsible AI use and data sensitivity across all engineering workflows.

Skills

Python Java JavaScript AI Machine Learning cloud-native CI/CD Software Development Life Cycle Automation System Design Application Development SDKs Frameworks Agile Secure Coding Automated Testing

What you'll do

Develop secure, high-quality production code and perform code reviews and debugging for other team members.
Design and execute creative software solutions to solve complex technical problems beyond conventional approaches.
Identify and automate the remediation of recurring issues to improve the operational stability of software systems.
Drive team adoption of enterprise-authorized AI-assisted engineering practices for code review, refactoring, and testing.
Establish consistent validation standards for secure coding, peer reviews, and automated testing across the team.
Build AI-native components with automated upgrades to ensure seamless adoption across the enterprise.
Lead communities of practice to drive awareness and adoption of leading-edge technologies and shared frameworks.
Apply SDLC toolchain knowledge to improve the value realized by automation and continuous delivery methods.

What we're looking for

Formal training or certification on software engineering concepts and 5+ years of applied experience.
Demonstrated experience leading the use of approved AI-assisted software development tools and validating AI outputs.
Strong understanding of responsible AI use, data sensitivity, and coaching engineers on safe, compliant adoption.
Hands-on practical experience delivering system design, application development, testing, and operational stability.
Advanced skills in Python.
Proficiency in automation, continuous delivery methods, and all aspects of the Software Development Life Cycle.
Advanced understanding of agile methodologies, including CI/CD, application resiliency, and security.
Demonstrated proficiency in a technical discipline such as cloud, artificial intelligence, or machine learning.
Practical cloud-native experience.
Advanced skills in Java and JavaScript (preferred).
Experience building SDKs, frameworks, or developer platforms for other engineering teams (preferred).
Experience with AI-native tooling and AI-assisted development workflows (preferred).
Demonstrated code shipped to production that leverages AI or builds AI capabilities (preferred).