Server & Storage Engineering Lead, Digital & Technology Services

Description

About Alvarez & Marsal

Alvarez & Marsal (A&M) is a global consulting firm with over 10,000 entrepreneurial, action and results-oriented professionals in over 40 countries. We take a hands-on approach to solving our clients' problems and assisting them in reaching their potential. Our culture celebrates independent thinkers and doers who positively impact our clients and shape our industry. The collaborative environment and engaging work—guided by A&M's core values of Integrity, Quality, Objectivity, Fun, Personal Reward, and Inclusive Diversity—are why our people love working at A&M.

The Team

Alvarez & Marsal's Corporate Performance Improvement practice is looking for a Server & Storage Engineering leader with deep expertise in enterprise compute and storage platforms, legacy system modernization, and infrastructure rationalization. This role requires someone who has driven server consolidation and storage optimization at enterprise scale - across mainframe, midrange, and x86 environments.

Experience Should Include

• Enterprise server platform architecture - x86, IBM z (mainframe), Unisys, P Series, SPARC, Itanium

• Storage platform architecture - SAN, NAS, object storage, tiered storage design, and capacity optimization

• Server consolidation, virtualization strategy, and legacy platform decommission planning

• Storage growth management, data tiering, and decommission targeting

• Hybrid infrastructure design - bridging on-premises compute/storage with cloud-based equivalents

• Federal infrastructure environments preferred - experience managing classified compute/storage platforms is a strong advantage given the complexity of multi-classification environments

• AI-assisted infrastructure analysis, capacity modeling, and optimization - must demonstrate active use of AI tools in delivery; AI fluency is required for this role

• Design and implement Kubernetes-native auto-scaling architectures across AWS, Azure, and GCP. Expert-level experience with HPA, VPA, and event-driven scaling (KEDA). Proven ability to balance predictive pre-scaling with reactive real-time capacity adjustments, optimizing sub-second response times while maintaining cost efficiency. Strong background in multi-cloud workload orchestration and resource right-sizing

How you will contribute

• Lead server and storage assessments - inventory analysis, utilization profiling, age/EOL mapping, and platform rationalization

• Develop legacy platform retirement roadmaps (mainframe, SPARC, Itanium) with clear decommission timelines, migration paths, and risk mitigation

• Analyze resource utilization patterns (CPU, memory, I/O, storage capacity) to identify rightsizing and consolidation opportunities

• Design target-state compute and storage architectures balancing cost, performance, availability, and security requirements

• Assess workload placement options across on-premises, private cloud, and commercial cloud for compute and storage workloads

• Integrate findings into A&M's broader engagement scope and deliverables

• Support practice development through internal training, thought leadership, and people development

Qualifications

• 8-12+ years of professional experience in enterprise server and storage engineering, with consulting or advisory delivery

• Demonstrated experience leading server consolidation or legacy platform migration programs at enterprise scale

• Deep understanding of mainframe economics and modernization trade-offs (rehost, replatform, refactor, retire)

• Federal infrastructure experience preferred - deep transformation experience in regulated industries can substitute

• Bachelor's degree required; relevant vendor certifications (IBM, Dell/EMC, Net App, VMware) valued

• Comfortable with travel up to 80%

• Full-time, contract, and project-based engagements available

What Distinguishes a Great Candidate

Has personally driven legacy platform retirement programs - not just assessed them. Understands mainframe-to-cloud economics and can articulate the trade-offs to executive audiences. Brings AI-assisted capacity analysis and optimization modeling as a standard part of the delivery toolkit. Knowledge of extinction risk on legacy platforms is real - this candidate has the…