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Salary
$154k – $312k per year (Estimated)
Location
In office (Columbus)
Seniority
Staff
Overview
Company
Impact
Profile match
JPMorgan Chase & Co. is a leading global financial services firm and the largest banking institution in the United States by assets. Headquartered in New York City, the company offers a comprehensive range of financial solutions, including investment banking, asset management, treasury services, and commercial banking. Through its widely recognized consumer division, Chase, it delivers retail banking, credit card, and mortgage services to tens of millions of households across the globe.

As a Lead Software Engineer at JPMorganChase within the Chief Technology Office for Engineering Services & Platforms (ESP), 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.

As a full-stack software and design lead in our Data & Control Plane (DCP) developer team, we look for people who are passionate about solving problems through innovation and engineering practices. You'll be required to apply your depth of knowledge and expertise to all aspects of the software development lifecycle, front end and back, as well as partner continuously with your stakeholders and more junior colleagues to keep us focused on common goals. We embrace a culture of experimentation and constantly strive for improvement and learning. You’ll work in a collaborative, trusting, thought-provoking environment-one that encourages diversity of thought and creative solutions that are in the best interests of our customers globally.

Job responsibilities

  • 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

  • Develops secure and high-quality production code, and reviews and debugs code written by others

  • 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.

  • 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

Required qualifications, capabilities, and skills

  • 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

  • Advanced in one or more programming language(s) - Java & React

  • Frontend expertise in developing UI applications
  • Experience with RESTful API design, data-driven design, microservices architecture, event-driven architecture, and enterprise integration patterns

  • Experience with messaging platforms and stream data processing - Kafka.

  • 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

  • Proficient in all aspects of the Software Development Life Cycle

  • Practical cloud native experience (AWS)

  • Knowledge of Containerization and Container Runtime/Orchestration platforms (Docker/Kubernetes/ECS etc.)

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