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Lead Software Engineer - Python Software Engineer

Job in Columbus, Franklin County, Ohio, 43224, USA
Listing for: JPMorgan Chase & Co.
Full Time position
Listed on 2026-10-04
Job specializations:
  • Software Development
    Software Engineer, DevOps, AI Engineer (Applied/Software), Cloud Engineer - Software
Salary/Wage Range or Industry Benchmark: 130000 - 180000 USD Yearly USD 130000.00 180000.00 YEAR
Job Description & How to Apply Below

We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible. As a Lead Software Engineer at JPMorgan

Chase within the Chief Technology Office, 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.

Job

responsibilities
  • 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.
  • 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.
  • Builds components to be drop-in and AI-native with automated upgrades so adopters across the enterprise stay current with minimal effort.
  • Leads communities of practice across Software Engineering to drive awareness and adoption of leading-edge technologies and shared frameworks.
  • Adds to team culture of diversity, opportunity, inclusion, and respect.
Required qualifications, capabilities, and skills
  • Formal training or certification on software engineering concepts and 5+ years applied experience.
  • 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.
  • Hands-on practical experience delivering system design, application development, testing, and operational stability.
  • Advanced skills in Python.
  • Proficiency in automation and continuous delivery methods.
  • Proficient in all aspects of the Software Development Life Cycle.
  • Advanced understanding of agile methodologies such as CI/CD, application resiliency, and security.
  • Demonstrated proficiency in a technical discipline such as cloud, artificial intelligence, or machine learning.
  • Practical cloud-native experience.
Preferred qualifications, capabilities, and skills
  • Advanced skills in Java, JavaScript.
  • Experience building SDKs, frameworks, or developer platforms that other engineering teams consume.
  • Experience with AI-native tooling and AI-assisted development workflows.
  • Demonstrated code shipped to production that leverages AI or builds AI capabilities.
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