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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # GPU Infrastructure Deployment Program Manager - **Company:** Orion Placement - **Location:** Pittsburgh, PA, United States (Remote available) - **Experience:** Experienced - **Salary:** $120,000.0 - $200,000.0 - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Asana, Confluence, JIRA, Computer Clusters, Data Centers, Microsoft Project, Network Architecture, Network Connections, Network Service, AI Infrastructure, Smartsheet, Hardware Infrastructure - **Published:** August 23, 2026 - **Apply:** https://www.careerjet.com/jobad/usca0c08675bcc838575e83777f698d7d0 ## About the Role * 7+ years of program or project management experience supporting data center, infrastructure, telecom, or large-scale technology deployments. * Direct experience managing GPU cluster deployments from planning through implementation or go-live. * Demonstrated experience managing multiple concurrent, complex infrastructure projects. * Strong understanding of GPU cluster architecture and the end-to-end deployment lifecycle. * Experience coordinating data center readiness, hardware delivery and installation, network turn-up, vendor dependencies, and acceptance testing. * Experience working directly with OEM manufacturers, data center operators, and network or connectivity providers. * Strong experience with risk, issue, dependency, and critical-path management. * Experience producing reporting for enterprise clients and executive or Board-level stakeholders. * Strong proficiency with complex project management tools such as Smartsheet, MS Project, Jira, Confluence, Asana, or similar platforms. * Excellent communication skills and the ability to work credibly with technical, operational, executive, and customer stakeholders. * Must be a US citizen. * PMP certification or equivalent is preferred. * Experience with a neocloud, hyperscaler, GPU infrastructure provider, or similar large-scale compute environment is strongly preferred. * Familiarity with NVIDIA Reference Architecture and cluster acceptance testing standards is a plus., In business and technology, "telco" can also refer to companies that provide network infrastructure, data connectivity, and communication APIs for enterprises. 8/19 They need to have this exp: Experience with multi-billion-dollar global deals, selling AI solutions to large enterprise clients, strong background in complex, consultative sales, comfortable managing long, sophisticated sales processes, able to handle a high volume of transactions at the same time. Recruiters don't submit anyone without GPU experience to AXE. Requirements: Must-have: Nationwide remote, 7+ yrs data center, infrastructure, telecom, or large-scale tech deployments PM exp, must have GPU cluster deployment exp (Y/N)must be US citizen, Minimum qualifications: Bachelor's degree in a technical field, or equivalent practical experience. 2 years of experience in program management. Experience building, auto… + 4 days ago ## Description Must have 7+ years of program or project management experience supporting data center, infrastructure, telecom, or large-scale technology deployments, along with direct GPU cluster deployment experience. Candidates must be US citizens and must have genuine fluency in the GPU cluster deployment lifecycle. Generic project management experience without hands-on exposure to GPU cluster deployments will not meet the requirements. About Us We are building next-generation AI infrastructure and deploying high-performance GPU clusters for enterprise customers. Our teams bring together data centers, OEMs, networking providers, hardware partners, and technical specialists to deliver complex infrastructure from initial planning through customer go-live. Confidential Employer., * Own program management for multiple concurrent GPU cluster deployments from contract signature through customer go-live. * Build and maintain detailed, dependency-aware project plans covering all deployment workstreams. * Track OEM hardware manufacturing, shipment, delivery, installation, and provisioning timelines. * Coordinate data center readiness, build-out, power, cooling, rack installation, and facility dependencies. * Manage network and connectivity dependencies, including coordination with network service providers. * Maintain clear visibility into project status, critical paths, risks, bottlenecks, dependencies, and mitigation plans across multiple simultaneous deployments. * Proactively identify issues before they impact deployment schedules or budgets and coordinate appropriate escalation. * Coordinate directly with OEM manufacturers, data center operators, network and connectivity providers, MSPs, and other external partners. * Partner closely with GPU cluster architecture, data center operations, procurement, supply chain, and deployment teams. * Produce clear progress reporting for enterprise clients and translate technical project status into meaningful go-live planning information. * Prepare executive and Board-level reporting summarizing deployment status, risks, dependencies, schedule impacts, and financial considerations. * Maintain working fluency across the GPU cluster deployment lifecycle, including data center readiness, hardware delivery and installation, network turn-up, provisioning, and acceptance testing. * Ask the right technical questions to identify schedule risk, missing dependencies, and potential bottlenecks early. * Ensure all deployment workstreams remain aligned and drive predictable contract-to-go-live timelines. ## Related Videos - [A Founder's Journey : From Startup Chaos to Purposeful Growth](https://www.wearedevelopers.com/videos/1926-a-founder-s-journey-from-startup-chaos-to-purposeful-growth) - [Improving quality with Agentic AI with Rovo Dev and Xray](https://www.wearedevelopers.com/videos/2005-improving-quality-with-agentic-ai-with-rovo-dev-and-xray) - [42 x 2 Canvases Later: Two Years, Two Minds, Many Lessons](https://www.wearedevelopers.com/videos/1458-42-x-2-canvases-later-two-years-two-minds-many-lessons) - [Your Next AI Needs 10,000 GPUs. 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