Lead Infrastructure Engineer - VMware

JPMorganChase•Columbus, OH

About The Position

Assume a vital position as a key member of a high-performing team that delivers infrastructure and performance excellence. Your role will be instrumental in shaping the future at one of the world's largest and most influential companies. As a Lead Infrastructure Engineer at JPMorganChase within Corporate Technology, you will serve as a subject matter expert on virtualization and operating system platforms, driving the stability, scalability, and performance of critical infrastructure. You will partner across application and infrastructure teams to identify risks, govern remediation efforts, and ensure end-to-end monitoring of systems running at scale. Your work will directly influence the reliability of platforms that support the firm's global operations, and your technical leadership will help shape team culture and engineering standards.

Requirements

Formal training or certification on infrastructure engineering concepts and advanced applied experience
Strong knowledge of one or more infrastructure disciplines, including VMware/ESXi, Linux/Unix, Microsoft Windows, hardware, networking, databases, storage engineering, deployment practices, integration, automation, scaling, resilience, or performance assessments
Proficiency in one or more scripting or automation languages such as Python, Terraform, Ansible, or equivalent tools
Demonstrated ability to drive growth in infrastructure engineering knowledge across additional domains, including data fluency and automation
Ability to make significant technical decisions on projects spanning multiple technologies and applications
Strong analytical and problem-solving skills with the ability to work independently on moderately complex infrastructure challenges
Demonstrated experience using enterprise-authorized AI capabilities within the work environment to support infrastructure engineering workflows with strong validation habits and awareness of data sensitivity.
Ability to review and validate AI-assisted recommendations before implementation, escalating when uncertain and ensuring outcomes align to resiliency, security, and auditability expectations.

Nice To Haves

Hands-on experience supporting and administering VMware vSphere ESXi hosts and vCenter environments
System administration experience with Linux, Unix, or Windows operating systems
Scripting or coding experience using tools and languages such as Terraform, Ansible, PowerShell, Java, Python, or Scala
Familiarity with enterprise tooling such as Jira, ServiceNow, Microsoft System Center Configuration Manager, or Windows Active Directory
Experience with capacity planning, performance monitoring, or infrastructure observability practices

Responsibilities

Serve as a subject matter expert on VMware (ESXi, vCenter) platforms and Linux environments, providing technical guidance across infrastructure initiatives
Apply technical knowledge and structured problem-solving methodologies to projects of moderate-to-high scope, with a focus on improving systems running at scale
Ensure end-to-end monitoring of applications and infrastructure, proactively identifying and resolving performance and availability issues
Resolve complex technical nuances independently and determine the appropriate escalation path when needed
Execute conventional and emerging approaches to decompose and solve infrastructure engineering challenges
Drive daily activities supporting standard capacity management processes and associated applications
Partner with application and infrastructure teams to identify potential capacity risks and govern the status of remediation efforts
Evaluate upstream and downstream data flows, systems dependencies, and technical implications when making architectural or operational decisions
Uses enterprise-authorized AI capabilities within the work environment to accelerate infrastructure analysis and design documentation, validating outputs and handling operational data according to sensitivity and security requirements.
Applies reuse-first, AI-assisted practices within delivery and automation routines to identify recurring issues and validate remediation options, ensuring changes are traceable/auditable and aligned to resiliency and security expectations.