JPMorgan Chase—Lead Software Engineer- Linux

Job description

Description: 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 Infrastructure Platforms 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 exhibit both depth and breadth of knowledge regarding software, applications, and technical processes across multiple technical disciplines. You also have a specialization in a specific domain within infrastructure engineering to drive programs or initiatives consisting of multiple technologies and applications. 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 - Test and certify new Red Hat operating systems using AI, create multiple image formats, and deliver end-to-end automation using Ansible, Terraform, Jenkins, Bash, and Python. - Build and maintain a firmwide Standard Operating Environment by creating standard OS images for virtual/physical servers, desktops, GPUs, and containers across on-prem and external clouds. - Provide services to host and manage software distribution (primarily RPMs) across all clouds, including testing and deployment to production. - Automate provisioning of Linux desktops for developers and streamline the testing and promotion pipeline for RPM packages. - Address complex technical issues, and design/develop integration components and REST APIs/microservices. - Drive adoption of enterprise-authorized AI-assisted engineering practices to improve code quality, delivery speed, and operational outcomes, while establishing consistent validation standards. - 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. - 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. 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 - Demonstrate strong Linux infrastructure development expertise (OS configuration, system hardening, kernel tuning, package management) across on-prem and cloud environments. - Show experience in cloud, hybrid, and virtualized infrastructure, and proficiency with modern software languages. - Design and implement infrastructure automation using Ansible Core or Ansible Automation Platform (playbooks, workflows, reusable roles/modules). - Apply hands-on experience with containers and Kubernetes-based orchestration, deploying and managing workloads in enterprise environments. - Use Python to build and maintain automation solutions, including working knowledge of CI/CD pipelines, source control, and build automation tools. - Support cross-platform infrastructure solutions with experience on Windows Server operating systems. - Build REST API–based microservices, and provide feedback on Ansible design, architecture, and deployment processes. - 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 practice Preferred qualifications, capabilities, and skills - Leverage knowledge of content delivery and repository management systems (e.g., Red Hat Satellite, Pulp, JFrog Artifactory) to manage software distribution and patch lifecycle. - Build or contribute to AI agents/skills and agentic workflows that integrate large language models into infrastructure tooling. - Apply knowledge of Citrix virtualization infrastructure to support enterprise platform needs. - Initiate and implement ideas to solve business problems and drive innovative solutions.