JPMorgan Chase
Sr Lead Infrastructure Engineer - Hyper-V Virtualization & Infrastructure Engineering
$162K–$210K
Jersey City, NJ +4 · Senior · Full-time · Posted Oct 2, 2026
- Location
- Jersey City, NJ
Plano, TX
Houston, TX
Seattle, WA
San Francisco, CA - Experience
- 5+ years of relevant hands-on experience.
- Education
- Formal training or certification in infrastructure disciplines.
About the job
Engineers and operates enterprise-scale Hyper-V infrastructure across global data centers, building resilient virtualization services and automation for large workloads.
What you'll do
- Design Hyper-V clusters and automate provisioning, configuration, patching, compliance, and decommissioning.
- Develop workload-management and orchestration capabilities, benchmark platform performance, and troubleshoot infrastructure across its stack.
- Harden and document the platform, apply validated AI-assisted practices, and mentor engineers.
What they ask for
- Formal training or certification in infrastructure disciplines, plus 5+ years of relevant hands-on experience in enterprise or large-scale environments.
- Deep Microsoft Hyper-V expertise at scale, including WSFC, live migration, S2D, and vSwitch/SET; strong PowerShell skills.
- Experience with full-stack performance auditing, virtualized storage optimization, and data-center-scale automation/configuration tooling.
- Production change and risk-management experience, working proficiency in C#/.NET or equivalent, CI/CD and automated testing experience, and demonstrated use and validation of enterprise-authorized AI capabilities.
Nice to have
- Experience operating VMware ESXi and/or KVM alongside Hyper-V.
- Experience with Microsoft System Center tooling, vulnerability remediation, or performance benchmarking tools.
Pay
USD 161,500.00-$210,000.00 base salary (Jersey City, NJ); USD 161,500.00-$210,000.00 base salary (Seattle, WA); USD 161,500.00-$210,000.00 base salary (San Francisco, CA)
Tools
Microsoft Hyper-V, WSFC, PowerShell, DSC, C#/.NET 8, SCCM, Ansible, VMware ESXi
AI focus
Uses enterprise-authorized AI to analyze infrastructure signals and document mitigation options, and adopts AI-assisted practices in delivery and automation. Requires validating recommendations and protecting sensitive data while maintaining resiliency, security, traceability, and auditability.
Model-written summary · the original posting is authoritative