You will set the deployment-engineering strategy for cluster build-out , how racks are organized into pods, halls, and sites; how compute, network, power, and cooling systems interface at the rack boundary; and how deployment scope flows cleanly from hardware specification to facility delivery to a running cluster.

This role is focused on deployment engineering, not on datacenter network or systems design , your scope is making sure clusters land cleanly and predictably, not designing the fabrics or facilities themselves.

You will work across hardware, networking, facilities, supply chain, and construction to ensure that every generation of accelerator we deploy lands in a datacenter that is ready for it , on schedule, at full density, and with every piece of required infrastructure accounted for.

You will be the person who sees around corners: anticipating how next-generation rack designs will stress our facilities, where our deployment model will break at scale, and what needs to change now so that the next cluster turn-up is faster and more predictable than the last.

You will operate at the intersection of engineering strategy and execution discipline, partnering with internal research and systems teams, external developers, engineering firms, and OEM partners to deliver cluster capacity at the speed the frontier demands.

Responsibilities:

• Own cluster-level deployment strategy , define how AI compute clusters are organized across the floor, how racks interconnect, and how cluster topology requirements translate into facility and deployment scope across a portfolio of sites.

• Set rack interface standards spanning power, network, mechanical, thermal, and spatial domains, and ensure that every deployment includes the complete set of infrastructure required to bring a cluster online.

• Drive multi-threaded cluster bring-up programs across hardware, networking, power, and cooling , owning plans, dependencies, and critical paths from hardware specification through energization and turn-up.

• Partner with internal engineering teams , research, systems, networking, and hardware , to translate cluster requirements into deployable facility scope, and to derisk onboarding of new hardware platforms well ahead of delivery.

• Lead external partner execution with developers, engineering firms, OEMs, and construction teams, driving technical reviews, deviation management, and handoffs that keep deployments on schedule and within specification.

• Improve cluster turn-up reliability and repeatability , identify systemic gaps in deployment scope, tooling, and partner interfaces, and drive durable fixes that reduce time-to-serve for new capacity.

• Define and track deployment KPIs , cluster readiness, schedule adherence, scope completeness, time-to-first-packet , and use historical trends to forecast risk and inform capacity planning.

• Coordinate cross-functional readiness across supply chain, security, operations, and construction to ship production-ready compute capacity.

• Provide crisp executive visibility on deployment progress, tradeoffs, and risks across a portfolio of concurrent cluster programs.

• Design cluster interfaces for durability , define rack and cluster-level interfaces that remain robust across hardware generations, so that facility scope and deployment models do not need to be reinvented every time the underlying hardware changes.

• Build cluster layout and BOM tooling , create and maintain the tools, templates, and data models that turn cluster topology and rack specifications into accurate floor layouts, deployment sequences, and complete bills of materials, replacing one-off spreadsheets with repeatable, auditable workflows.

You may be a good fit if you:

• Have 10+ years of experience in hyperscale datacenter environments, with senior-level responsibility for cluster deployment, large-scale IT integration, or equivalent infrastructure programs.

• Have delivered AI, HPC, or high-density compute clusters at scale and developed a strong intuition for the constraints that govern cluster deployment , interconnect reach, adjacency, power density, and thermal limits.

• Can operate fluently across the boundary between IT hardware and facility infrastructure, and have set interface standards that held up across multiple hardware generations and sites.

• Have led cross-functional programs with both internal engineering teams and external developers, engineering firms, and OEM partners, and are effective at driving alignment across organizational levels.

• Combine strong systems thinking with execution discipline , comfortable zooming from cluster topology and portfolio strategy down to the specific interface detail that will otherwise become a field issue.

• Communicate clearly with technical and executive audiences, and can distill complex, multi-disciplinary programs into decisions and tradeoffs leadership can act on.

• Thrive in ambiguous, fast-moving environments where the hardware, the scale, and the requirements are all changing simultaneously.

• Hold a Bachelor's degree in Electrical Engineering, Mechanical Engineering, Computer Engineering, or equivalent practical experience.

Strong candidates may also:

• Have direct experience deploying leading-edge AI accelerator clusters at hyperscale.

• Have shaped reference designs, deployment standards, or cluster-level playbooks that were adopted across a fleet.

• Have experience working across multiple geographies and understand how regional codes, climate, utility constraints, and supply chains shape cluster-level decisions.

• Have partnered closely with hardware and system providers on long-term platform onboarding and bring-up.

• Have experience building the program mechanisms , roadmaps, milestones, risk registers, runbooks , that make delivery predictable at massive scale.

The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings (“OTE”) range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.

Annual Salary: $320,000-$405,000 USD

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You will set the deployment-engineering strategy for cluster build-out , how racks are organized into pods, halls, and sites; how compute, network, power, and cooling systems interface at the rack boundary; and how deployment scope flows cleanly from hardware specification to facility delivery to a running cluster.

This role is focused on deployment engineering, not on datacenter network or systems design , your scope is making sure clusters land cleanly and predictably, not designing the fabrics or facilities themselves.

You will work across hardware, networking, facilities, supply chain, and construction to ensure that every generation of accelerator we deploy lands in a datacenter that is ready for it , on schedule, at full density, and with every piece of required infrastructure accounted for.

You will be the person who sees around corners: anticipating how next-generation rack designs will stress our facilities, where our deployment model will break at scale, and what needs to change now so that the next cluster turn-up is faster and more predictable than the last.

You will operate at the intersection of engineering strategy and execution discipline, partnering with internal research and systems teams, external developers, engineering firms, and OEM partners to deliver cluster capacity at the speed the frontier demands.

Responsibilities:

• Own cluster-level deployment strategy , define how AI compute clusters are organized across the floor, how racks interconnect, and how cluster topology requirements translate into facility and deployment scope across a portfolio of sites.

• Set rack interface standards spanning power, network, mechanical, thermal, and spatial domains, and ensure that every deployment includes the complete set of infrastructure required to bring a cluster online.

• Drive multi-threaded cluster bring-up programs across hardware, networking, power, and cooling , owning plans, dependencies, and critical paths from hardware specification through energization and turn-up.

• Partner with internal engineering teams , research, systems, networking, and hardware , to translate cluster requirements into deployable facility scope, and to derisk onboarding of new hardware platforms well ahead of delivery.

• Lead external partner execution with developers, engineering firms, OEMs, and construction teams, driving technical reviews, deviation management, and handoffs that keep deployments on schedule and within specification.

• Improve cluster turn-up reliability and repeatability , identify systemic gaps in deployment scope, tooling, and partner interfaces, and drive durable fixes that reduce time-to-serve for new capacity.

• Define and track deployment KPIs , cluster readiness, schedule adherence, scope completeness, time-to-first-packet , and use historical trends to forecast risk and inform capacity planning.

• Coordinate cross-functional readiness across supply chain, security, operations, and construction to ship production-ready compute capacity.

• Provide crisp executive visibility on deployment progress, tradeoffs, and risks across a portfolio of concurrent cluster programs.

• Design cluster interfaces for durability , define rack and cluster-level interfaces that remain robust across hardware generations, so that facility scope and deployment models do not need to be reinvented every time the underlying hardware changes.

• Build cluster layout and BOM tooling , create and maintain the tools, templates, and data models that turn cluster topology and rack specifications into accurate floor layouts, deployment sequences, and complete bills of materials, replacing one-off spreadsheets with repeatable, auditable workflows.

You may be a good fit if you:

• Have 10+ years of experience in hyperscale datacenter environments, with senior-level responsibility for cluster deployment, large-scale IT integration, or equivalent infrastructure programs.

• Have delivered AI, HPC, or high-density compute clusters at scale and developed a strong intuition for the constraints that govern cluster deployment , interconnect reach, adjacency, power density, and thermal limits.

• Can operate fluently across the boundary between IT hardware and facility infrastructure, and have set interface standards that held up across multiple hardware generations and sites.

• Have led cross-functional programs with both internal engineering teams and external developers, engineering firms, and OEM partners, and are effective at driving alignment across organizational levels.

• Combine strong systems thinking with execution discipline , comfortable zooming from cluster topology and portfolio strategy down to the specific interface detail that will otherwise become a field issue.

• Communicate clearly with technical and executive audiences, and can distill complex, multi-disciplinary programs into decisions and tradeoffs leadership can act on.

• Thrive in ambiguous, fast-moving environments where the hardware, the scale, and the requirements are all changing simultaneously.

• Hold a Bachelor's degree in Electrical Engineering, Mechanical Engineering, Computer Engineering, or equivalent practical experience.

Strong candidates may also:

• Have direct experience deploying leading-edge AI accelerator clusters at hyperscale.

• Have shaped reference designs, deployment standards, or cluster-level playbooks that were adopted across a fleet.

• Have experience working across multiple geographies and understand how regional codes, climate, utility constraints, and supply chains shape cluster-level decisions.

• Have partnered closely with hardware and system providers on long-term platform onboarding and bring-up.

• Have experience building the program mechanisms , roadmaps, milestones, risk registers, runbooks , that make delivery predictable at massive scale.

The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings (“OTE”) range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.

Annual Salary: $320,000-$405,000 USD

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The ideal candidate has experience supporting construction projects, managing contractor sourcing, coordinating bids, and working cross-functionally with engineers, and project teams to ensure projects are delivered on time and within budget.

This role will play a key part in supporting new facility development and expansion projects as Shield AI continues to scale.

Responsibilities:

• Lead sourcing and procurement activities for construction and facility expansion projects, including contractor selection, bid management, and vendor negotiations.

• Partner with Facilities, Engineering, and Operations teams to support the development and build-out of new manufacturing and engineering facilities.

• Manage RFPs/RFQs for construction vendors, general contractors, and specialty subcontractors, evaluating proposals based on cost, capability, and schedule.

• Negotiate pricing, contracts, and project terms with construction suppliers and service providers.

• Coordinate with site selection partners, project managers, and internal stakeholders to ensure procurement activities align with project timelines.

• Manage purchase orders, contracts, and supplier performance within the company's ERP system (Deltek Costpoint).

• Track project procurement milestones, delivery schedules, and contractor performance to support successful project execution.

• Support the development of standard procurement processes for construction and capital project sourcing.

• Ensure vendor compliance with company policies and procurement standards.

Requirements:

• 3–7 years of experience in procurement, sourcing, or supply chain, with exposure to construction, facilities, or capital project procurement.

• Experience sourcing or managing suppliers for construction projects, facility expansions, or infrastructure development.

• Familiarity with general contractors, subcontractors, and construction bid processes (RFP/RFQ).

• Strong negotiation skills with the ability to manage supplier pricing, contracts, and project terms.

• Excellent organizational and project coordination skills.

• Strong communication skills with the ability to collaborate across engineering, operations, and project teams.

• Proficiency in Microsoft Excel and procurement systems or ERP platforms.

Preferences:

• Experience supporting manufacturing facility construction, plant expansions, or engineering lab build-outs.

• Background working with general contractors, or construction project teams.

• Experience sourcing capital equipment, tooling, or facility infrastructure.

• Experience working in aerospace, defense, manufacturing, or high-tech environments.

• Familiarity with Deltek Costpoint or other ERP systems used for procurement.

• Knowledge of FAR/DFARS or compliance-driven procurement environments.

Why This Role is Unique:

• Opportunity to support major facility expansion projects as Shield AI continues to grow.

• Work closely with engineering, facilities, and leadership teams to help build the infrastructure supporting next-generation autonomous systems.

• Join a fast-growing company where procurement professionals can directly impact large-scale projects and operational growth.

Salary: $65,000 - $105,000 a year

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