Lead Software Engineer- Linux

Job 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.

Work arrangement
No