Senior Server & Storage Engineering Lead | AI-Driven Infra

Alvarez & Marsal; Dallas (TX); On-site; USD 135,000 - 210,000; Full time

Job summary

Alvarez & Marsal (A&M) seeks a Server & Storage Engineering leader to guide enterprise compute/storage modernization across mainframe, midrange, and x86 environments. You will drive consolidation, virtualization, and decommissioning programs with a focus on AI-assisted capacity analysis and cloud integration.

Ideal candidates have 8–12+ years of experience, a strong foundation in mainframe economics, and a track record of governing complex modernization in regulated settings.

Qualifications

• 8-12+ years in enterprise server and storage engineering, with consulting or advisory delivery.
• Experience leading server consolidation or legacy platform migration programs at scale.
• Understanding of mainframe economics and modernization trade-offs.
• Federal infrastructure experience preferred; regulated environments valued.

Responsibilities

• Lead server and storage assessments: inventory analysis and platform rationalization.
• Develop legacy retirement roadmaps with migration paths and risk mitigation.
• Analyze resource utilization to identify rightsizing and consolidation opportunities.
• Design target-state compute/storage architectures balancing cost, performance, security.
• Assess workload placements across on-prem, private, and public clouds.

Skills

Enterprise server engineering

Storage engineering

Server consolidation

Legacy platform migration

Kubernetes & multi-cloud

AI-assisted capacity analysis

Cost optimization

Education

Bachelor's degree

Vendor certifications (IBM, Dell/EMC, NetApp, VMware)

Tools

IBM z mainframe

Dell/EMC storage

NetApp storage

VMware

Kubernetes (KEDA, HPA, VPA)

Job description

Alvarez & Marsal (A&M) seeks a Server & Storage Engineering leader to guide enterprise compute/storage modernization across mainframe, midrange, and x86 environments. You will drive consolidation, virtualization, and decommissioning programs with a focus on AI-assisted capacity analysis and cloud integration.

Ideal candidates have 8–12+ years of experience, a strong foundation in mainframe economics, and a track record of governing complex modernization in regulated settings.