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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Remote Senior Product Manager - GPU Products & AI Infrastructure - **Company:** Global Partnerships - **Location:** Cambridge, MA, United States - **Experience:** Expert - **Salary:** $136,200.0 - $204,200.0 - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Computing Platforms, Cloud Computing, Nvidia CUDA, InfiniBand, Cloud Services, AI Infrastructure, High Performance Computing, Information Technology, Data Analytics, Hardware Infrastructure - **Published:** August 22, 2026 - **Apply:** https://www.careerjet.com/jobad/us47f86f4af063891a4827c156b55dcfd0 ## About the Role To land this role, you must possess a rare blend of deep hardware-level intelligence and hyperscale product management acumen. We are filtering for candidates who meet the following high-bar criteria: * Professional Experience: 12+ years of relevant product management, technology, or engineering experience in massive-scale cloud or hardware ecosystems. * Target Domain Expertise: Direct, hands-on experience managing GPU cloud infrastructure or accelerated computing products. * AI & Accelerated Computing: Strong technical understanding of GPU architectures (e.g., NVIDIA, AMD), CUDA, and accelerated computing platforms. * Cluster Orchestration: Deep experience with AI/HPC workloads and GPU cluster orchestration (including resource management, fabric, interconnects like NVLink/InfiniBand, and large-scale GPU deployments). * Financial Mastery: Proven capability in developing complex business and financial frameworks for infrastructure, including pricing, TCO, or profitability models. * Advanced Infrastructure Literacy: Deep knowledge of AI workload patterns, enterprise security requirements, and hardware-level APIs related to GPU infrastructure. * Execution & Leadership: A strong customer-first mindset with a hyper-focus on automation, usability, and low-friction integration for data scientists. Exceptional ability to gain buy-in from highly technical engineering teams. * Education: Bachelor's degree in Computer Science, Engineering, or equivalent deeply technical practical experience ## Description * GPU Strategy & Vision: Define the product strategy, vision, and roadmap for next-generation GPU instances, high-performance clusters, and cloud services. [ , ] * Workload Architecture: Translate complex AI, HPC, graphics, and accelerated-computing workloads into rigid product specifications, performance requirements, and technical architectures. * Lifecycle & Investment: Guide the evolution of GPU infrastructure and make data-driven decisions around platform investments, resource management, and lifecycle management from concept to end-of-life. * Cloud Economics: Develop advanced business cases, financial models, pricing strategies, profitability analyses, and TCO models to aggressively support product investments. * Ecosystem Partnership: Partner directly with primary GPU technology and ecosystem providers to align roadmaps, integrations, and bleeding-edge technical requirements. * Go-To-Market Execution: Develop and execute comprehensive go-to-market strategies, including product messaging, positioning, launch plans, and customer engagement alongside sales and solutions engineering. * User Advocacy: Represent the direct needs of enterprise customers, engineers, and data scientists by identifying opportunities to improve automation, orchestration, monitoring, and usability. ## Related Videos - [Coffee with Developers - Stephen Jones - NVIDIA](https://www.wearedevelopers.com/videos/1303-coffee-with-developers-stephen-jones-nvidia) - [Accelerating Python on GPUs](https://www.wearedevelopers.com/videos/859-accelerating-python-on-gpus) - [The Gashlycrumb Tinies of AI Networking You Must Know (or Languish!)](https://www.wearedevelopers.com/videos/2067-the-gashlycrumb-tinies-of-ai-networking-you-must-know-or-languish) - [Leverage Cloud Computing Benefits with Serverless Multi-Cloud ML ](https://www.wearedevelopers.com/videos/78-leverage-cloud-computing-benefits-with-serverless-multi-cloud-ml) - [A Deep Dive on How To Leverage the NVIDIA GB200 for Ultra-Fast Training and Inference on Kubernetes](https://www.wearedevelopers.com/videos/1625-a-deep-dive-on-how-to-leverage-the-nvidia-gb200-for-ultra-fast-training-and-inference-on-kubernetes) - [WWC24 - Ankit Patel - Unlocking the Future Breakthrough Application Performance and Capabilities with NVIDIA](https://www.wearedevelopers.com/videos/920-wwc24-ankit-patel-unlocking-the-future-breakthrough-application-performance-and-capabilities-with-nvidia) ## Related Articles - [7 Cloud Computing Trends Coming in 2025 for Developers](https://www.wearedevelopers.com/magazine/412-7-cloud-computing-trends-coming-in-2025-for-developers) - [Best US AI Conferences for CTOs in 2026: Build vs. Buy, Vendor Evaluation, and Peer Intelligence](https://www.wearedevelopers.com/magazine/736-best-us-ai-conferences-for-ctos-in-2026-build-vs-buy-vendor-evaluation-and-peer-intelligence) - [Stephan Gillich - Bringing AI Everywhere](https://www.wearedevelopers.com/magazine/489-stephan-gillich-bringing-ai-everywhere) - [Got AI ideas but no money? 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