AI Consultant, Development & Asset Lifecycle
New
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Evolution Cloud Services (EVOCS)Data Center Infrastructure
This position is remote first. If located in Colorado or Metro Denver is helpful, not required.Full-TimeMiddle
Salary200,000 - 215,000 USD per year
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Job Details
- Experience
- 5–7+ years
- Required Skills
- Project ManagementArtificial IntelligenceCross-functional collaboration
Requirements
- 5–7+ years of experience across multiple phases of the data center or infrastructure asset lifecycle (development, construction, operations).
- Practical AI knowledge including familiarity with digital twins, predictive analytics, and cross-system data integration.
- Deep understanding of the data center asset lifecycle from market identification through design, construction, commissioning, operations, and capital reinvestment.
- Experience with project management platforms, BIM tools, construction management software, and CMMS/EAM systems.
- Demonstrated ability to work across organizational boundaries and solve process breakdowns at functional seams.
- Strong systems thinking capabilities to understand how decisions in one phase impact long-term asset performance.
- Ability to thrive in ambiguous environments and manage cross-functional relationships.
- Ability to travel 25–35% for site visits and relationship building.
Responsibilities
- Embed across the asset lifecycle to conduct structured discovery sessions and listening tours with key stakeholders.
- Translate lifecycle challenges into preliminary AI use cases, assessing feasibility across project systems, BIM models, and operational platforms.
- Build a champion network across functional boundaries to identify pain points and opportunity areas.
- Validate AI opportunities by evaluating business value, lifecycle cost optimization, and operational readiness impact.
- Develop detailed intake documentation for validated AI opportunities to support downstream prototyping teams.
- Facilitate cross-functional workshops to foster a continuous digital thread from development through operations.
- Identify patterns where insights from one lifecycle phase inform another to improve end-to-end performance.
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