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Senior Product Manager, AI Infrastructure, GPU
Akamai TechnologiesSenior Product Manager defining product strategy for GPU products at Akamai. Focused on managing product lifecycle, go-to-market strategies, and collaboration with ecosystem partners.
Posted 7/14/2026full-timeRemote • Massachusetts • 🇺🇸 United StatesSenior💰 $139,300 - $250,700 per yearWebsite
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in defining product strategy and managing the lifecycle of GPU instances and services, with a strong focus on developing go-to-market strategies and collaborating with partners. Proficient in translating technical needs into actionable specifications and performance goals while overseeing GPU infrastructure and implementing data-driven enhancements.
Highest-signal resume keywords
GPU Architecture ExpertiseCUDA Ecosystem ProficiencyCloud Networking KnowledgeAI Workload FamiliarityBusiness Model Development
ATS Keywords
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Hard Skills
Product Strategy DefinitionLifecycle ManagementGo-To-Market Strategy DevelopmentTechnical Specification TranslationData-Driven Decision Making
Soft Skills
CollaborationRelationship Management
Tools & Technologies
Accelerated Computing PlatformsGPU InterconnectsInfrastructure Redundancy
Industry Keywords
AIHPCGraphics WorkloadEnterprise Security RequirementsHardware-Level APIs
Tech Stack
Tools & technologiesCloud
About the role
Key responsibilities & impact- Define product strategy and roadmap for GPU instances, clusters, and services
- Manage the entire product lifecycle from planning to end-of-life
- Develop and execute go-to-market strategies, messaging, and launch plans
- Collaborate with ecosystem partners on roadmap and technical needs
- Translate AI, HPC and graphics workload needs into specifications and performance goals
- Oversee GPU infrastructure lifecycle components and implement data-driven decisions
- Identify enhancements for proactive monitoring and support processes
Requirements
What you’ll need- 12 years of relevant experience
- Bachelor's degree in Computer Science, Engineering, or its equivalent
- Expertise in GPU architectures, CUDA ecosystem, and accelerated computing platforms
- Knowledge of cloud networking, GPU interconnects, and infrastructure redundancy
- Proficiency in developing business and technical models for GPU cloud products
- Familiarity with AI workload patterns, enterprise security requirements, and hardware-level APIs
- Strong relationships with engineering teams regarding new GPU product goals
Benefits
Comp & perks- Health insurance
- 401K savings plan
- Paid time off (PTO)
- Sick time
- Family friendly benefits including parental leave
- Employee assistance program
- Focus on mental and financial wellness
- Equity awards and Employee Stock Purchase Plan (ESPP)