220260-en_US
About the role
The Services Architect – AI Data Center is the technical services counterpart to the Services Specialist, responsible for translating complex AI Data Center customer requirements into scalable, executable, and commercially sound Professional Services solutions. The role supports the full services pursuit lifecycle—from discovery and scope definition through solution design, estimating, statement of work development, technical closure, and transition to delivery. The ideal candidate understands how large-scale AI Data Center programs are actually delivered across integration centers and customer sites, including rack integration, fiber and structured cabling, infrastructure deployment, cluster bring-up, testing and validation, project/program management, logistics, and lifecycle services.
What you'll be doing
- Partner directly with the Services Specialist to develop Professional Services opportunities across strategic AI Data Center customers and programs.
- Lead services discovery sessions to understand customer scope, deployment model, schedule, volumes, site conditions, technical dependencies, and desired outcomes.
- Translate customer requirements into an end-to-end services architecture, delivery methodology, resource model, assumptions, dependencies, and acceptance criteria.
- Design services solutions spanning integration center activities, onsite deployment, rack integration, fiber/structured cabling, compute/network/storage implementation, testing, validation, and operational handoff.
- Develop detailed scopes of work, work breakdown structures, labor models, resource plans, skill requirements, schedules, deliverables, and responsibility matrices.
- Support estimating and pricing by defining labor assumptions, productivity rates, staffing profiles, travel requirements, equipment/tooling, partner content, and delivery risk.
- Develop scalable delivery models for large multi-site and high-volume AI Data Center programs, including repeatable deployment waves and standardized methods of procedure.
- Coordinate with Solution Architects across Fiber, Rack Integration, Compute, Network, and Storage to ensure the technical architecture and services scope are fully aligned.
- Engage Professional Services delivery, RDD, project management, operations, integration centers, supply chain, and partners to validate solution feasibility and capacity.
- Identify delivery risks, customer dependencies, scope gaps, assumptions, and commercial exposure before contract signature.
- Support RFQs/RFPs, proposals, customer workshops, technical presentations, SOW reviews, and services solution defense.
- Own the technical services handoff from presales into delivery and help ensure sold scope, assumptions, financial model, and customer commitments are understood by the execution team.
- Develop reusable services offerings, reference scopes, estimating models, delivery playbooks, and standardized methodologies for the AI Data Center Business.
- AI Data Center deployment and integration services
- Offsite rack integration, staging, configuration, and pre-build
- Onsite rack installation and infrastructure deployment
- Fiber, structured cabling, patching, testing, and remediation
- GPU / compute, network, and storage implementation services
- Cluster bring-up, configuration, acceptance testing, and validation
- High-density and liquid-cooled infrastructure deployment
- Project and program management / PMO
- Site readiness, deployment planning, and mobilization
- Logistics, material coordination, and deployment sequencing
- QA/QC, documentation, as-builts, and customer acceptance
- Day 2, lifecycle, optimization, and recurring services
What you'll be doing
- 7+ years of experience in Professional Services architecture, services presales, data center consulting, infrastructure deployment, technical program delivery, or a related role.
- Strong background designing and scoping complex technology Professional Services engagements.
- Experience supporting data center, hyperscale, cloud, AI infrastructure, HPC, or other large-scale infrastructure deployment programs.
- Strong understanding of how compute, networking, storage, rack integration, fiber, power, cooling, and physical data center infrastructure come together during deployment.
- Demonstrated experience developing statements of work, labor estimates, resource models, schedules, assumptions, deliverables, acceptance criteria, and responsibility matrices.
- Ability to translate technical architecture into a practical delivery plan with clearly defined tasks, skills, effort, dependencies, and risks.
- Experience estimating large field services or Professional Services engagements using productivity assumptions, unit rates, staffing models, and deployment volumes.
- Understanding of integration center / factory services and the relationship between offsite pre-integration and onsite deployment.
- Experience with subcontractors, strategic partners, or variable labor models supporting geographically distributed delivery is strongly preferred.
- Strong commercial awareness, including scope control, change management, margin, risk, utilization, and delivery economics.
- Strong customer-facing communication, workshop facilitation, technical writing, and presentation skills.
- Ability to operate across sales, architecture, engineering, Professional Services, RDD, operations, project management, sourcing, partners, and field delivery.
- AI CSP, hyperscale, NCP / neocloud, HPC, or large cloud infrastructure programs
- Large-scale GPU infrastructure deployments
- Rack integration and pre-build services
- High-volume fiber and structured cabling deployments
- Data center compute, network, and storage implementation
- Cluster build, acceptance, validation, and production handoff
- Liquid-cooled and high-density AI infrastructure
- Multi-site deployment programs with aggressive schedules
- Service center / integration center operating models
- PMO and complex program governance
- Partner-led and blended workforce delivery models
- Development of repeatable services methodologies and standardized SOWs
- Services Architecture – Converts complex customer requirements into a complete and executable Professional Services solution.
- Scoping & Estimating – Defines the work, resources, effort, assumptions, dependencies, and cost required to deliver successfully.
- AI Data Center Knowledge – Understands the deployment requirements associated with GPU compute, network, storage, racks, fiber, power, and cooling.
- Design-to-Deliver Thinking – Ensures the proposed solution can actually be mobilized, executed, tested, accepted, and scaled.
- Commercial Acumen – Balances customer outcomes with scope discipline, delivery risk, margin, and commercial viability.
- Customer Engagement – Leads discovery, solution workshops, scope reviews, and technical/commercial services discussions.
- Cross-Functional Leadership – Connects sales and solution architecture with Professional Services, RDD, operations, partners, and delivery.
- Standardization & Scale – Builds repeatable service models that can support very large AI Data Center programs.
- Services pipeline supported and converted
- Quality and accuracy of Professional Services solutions and SOWs
- Accuracy of labor, resource, and delivery estimates
- Services contribution and margin performance
- Reduction in scope gaps, delivery surprises, and unplanned change
- Speed from customer requirement to executable services solution
- Successful transition from presales into delivery
- Customer confidence in the proposed delivery model
- Development and adoption of repeatable AI Data Center service offerings
- Alignment between Services Specialists, technical architects, and delivery teams
The ideal candidate is a services-focused architect who understands both the technical requirements of AI infrastructure and the operational realities of deploying it at scale. They should be able to take a customer requirement or technical architecture and determine exactly how the organization will deliver it—what work must be performed, where it should be performed, what skills and resources are required, how long it will take, what it will cost, and what risks and dependencies must be managed. This individual should be a strong partner to the Services Specialist: the Services Specialist drives the customer relationship, opportunity, and commercial pursuit, while the Services Architect owns the technical services solution, scope, methodology, estimating inputs, and design-to-delivery integrity.
