Linux/SDET engineer Organization

What You’ll Do

• Define the product strategy, vision, and roadmap for GPU instances, clusters, and cloud services.
• Align product positioning, requirements, and priorities with customer needs, market trends, and business objectives.
• Manage the full product lifecycle, from initial planning and launch through ongoing optimization and eventual end-of-life.
• Develop business cases, financial models, pricing strategies, profitability analyses, and TCO models to support product investments and decisions.
• Develop and execute go-to-market strategies, including product messaging, positioning, launch plans, and customer engagement in partnership with marketing, sales, and solutions engineering.
• Partner with GPU technology and ecosystem providers to align roadmaps, integrations, and technical requirements.
• Translate AI, HPC, graphics, and other accelerated-computing workloads into product specifications, performance requirements, and technical architectures.
• Guide the evolution of GPU infrastructure and make data-driven decisions around platform investments and lifecycle management.
• Represent the needs of customers, engineers, and data scientists by identifying opportunities to improve usability, automation, monitoring, support, and maintenance processes.
• Build strong relationships with engineering teams and secure alignment around product goals, technical requirements, and future GPU capabilities.

• 12+ years of relevant product management, technology, or engineering experience and a bachelor’s degree in computer science, Engineering, or equivalent experience.
• Strong technical understanding of GPU architectures, CUDA, and accelerated computing platforms.
• Experience with GPU resource management and cluster orchestration for AI and high-performance computing workloads.
• Knowledge of cloud networking, GPU interconnects, infrastructure redundancy, and large-scale GPU deployments.
• Experience developing both technical and business models for GPU/cloud products, including pricing, profitability, and Total Cost of Ownership (TCO) analysis.
• Understanding of AI workload patterns, enterprise security requirements, and hardware-level APIs related to GPU infrastructure.
• A strong customer-first mindset, with a focus on automation, usability, and low-friction integration for GPU workloads.
• Proven ability to collaborate with highly technical engineering and data science teams and gain buy-in for new product initiatives.
• Strong communication, strategic thinking, and stakeholder management skills.
• Ability to balance complex technical requirements with customer needs and business objectives.

Why This Opportunity?

This is an opportunity to help shape the future of AI and accelerated computing in the cloud. You’ll play a key role in defining GPU products and services designed to support demanding AI, HPC, graphics, and enterprise workloads at global scale.

You’ll work at the intersection of product strategy, AI infrastructure, cloud computing, and advanced GPU technology, partnering with engineering and technology leaders to bring innovative products to market.

Remote & Flexibility

This is a remote position offering flexibility and the opportunity to work with a highly distributed team. The company supports employees in working in the environment where they can do their best work.

If you’re a technically minded product leader with deep experience in GPUs, AI infrastructure, cloud computing, and accelerated workloads, and you’re excited about building products that enable the next generation of AI applications, we’d love to hear from you.

Must Have

12+ years of relevant product management, technology, or engineering experience and a bachelor’s degree in computer science, Engineering, or equivalent experience.

Strong technical understanding of GPU architectures, CUDA, and accelerated computing platforms.

Experience with GPU resource management and cluster orchestration for AI and high-performance computing workloads.

Knowledge of cloud networking, GPU interconnects, infrastructure redundancy, and large-scale GPU deployments.

Experience developing both technical and business models for GPU/cloud products, including pricing, profitability, and Total Cost of Ownership (TCO) analysis.

Understanding of AI workload patterns, enterprise security requirements, and hardware-level APIs related to GPU infrastructure.

A strong customer-first mindset, with a focus on automation, usability, and low-friction integration for GPU workloads.

Proven ability to collaborate with highly technical engineering and data science teams and gain buy-in for new product initiatives.

Strong communication, strategic thinking, and stakeholder management skills.

Ability to balance complex technical requirements with customer needs and business objectives. Remote

Skills: Analysis Skills, Application Programming Interface (API), Artificial Intelligence (AI), Automation, Business Case, Business Model, CUDA (Compute Unified Device Architecture), Cloud Computing, Communication Skills, Computer Science, Computer Systems, Data Science, Ecosystems, Engineering, Enterprise Protection, Financial Modeling, GPU (Graphics Processing Unit), Graphics, Investment Management, Linux Operating System, Market Entry Strategy, Market Trend Analysis, Marketing, Marketing/Promotional Messaging, Product Design, Product Development, Product Lifecycle Management, Product Management, Product Positioning, Product Pricing, Product Programs, Product Strategy, Product Support, Product/Service Launch, Profit & Loss, Profit & Loss Analysis, Resource Management, Software Design for Test (SDET), Software Engineering, Solution Sales, Team Player, Total Cost of Ownership, Usability Engineering