Senior Product Manager – GPU Products, AI Infrastructure

This is a fully remote position, open to applicants in Massachusetts.

📋 Description

• Establish the product strategy, vision, and roadmap for next-generation GPU instances, high-performance clusters, and cloud services.

• Convert AI, HPC, graphics, and accelerated-computing workloads into product specifications, performance requirements, and technical frameworks.

• Direct the evolution of GPU infrastructure and utilize data-driven insights to make informed decisions regarding platform investments, resource management, and lifecycle management from inception to end-of-life.

• Create business cases, financial models, pricing strategies, profitability analyses, and TCO models to back product investments.

• Collaborate with key GPU technology and ecosystem providers to synchronize roadmaps, integrations, and technical prerequisites.

• Formulate and implement go-to-market strategies, encompassing product messaging, positioning, launch plans, and customer engagement with sales and solutions engineering.

• Advocate for enterprise customer, engineer, and data scientist requirements by pinpointing enhancements in automation, orchestration, monitoring, and usability.

⛳️ Requirements

• Over 12 years of pertinent product management, technology, or engineering experience within large-scale cloud or hardware ecosystems.

• Direct, hands-on experience in managing GPU cloud infrastructure or accelerated computing products.

• Solid technical knowledge of GPU architectures (e.g., NVIDIA, AMD), CUDA, and accelerated computing platforms.

• Extensive experience with AI/HPC workloads and GPU cluster orchestration, including resource management, fabric, NVLink/InfiniBand interconnects, and large-scale GPU deployments.

• Proven track record in creating intricate business and financial frameworks for infrastructure, including pricing, TCO, or profitability models.

• Comprehensive understanding of AI workload patterns, enterprise security needs, and hardware-level APIs associated with GPU infrastructure.

• Strong customer-centric approach with an emphasis on automation, usability, and seamless integration for data scientists.

• Exceptional aptitude for securing buy-in from highly technical engineering teams.

• Bachelor's degree in Computer Science, Engineering, or equivalent substantial technical practical experience.

🏝️ Benefits

• Competitive salary and performance-based bonuses.

• Comprehensive health, dental, and vision insurance.

• Generous vacation and paid time off policies.

• Opportunities for professional development and continuous learning.

• Flexible work arrangements and a supportive work environment.