Outbound Product Manager at Zettabyte

Job description

Overview We are seeking a Customer Solutions Manager or Outbound Product Manager who combines deep technical understanding of GPU cloud infrastructure with strong customer and market insight. This individual will engage directly with enterprise and AI customers, analyze competitive offerings, and bring structured, data-driven input into our product and go-to-market strategy. Key Responsibilities - Customer Engagement: Work directly with enterprise customers, AI developers, and ecosystem partners to understand workload patterns, pain points, and technical requirements. - Competitive and Market Analysis: Continuously track and analyze GPU cloud competitors (e.g., CoreWeave, Lambda, RunPod, AWS, Azure, GCP) across performance, cost, scalability, and customer experience. - Framework Insight: Maintain deep understanding of industry evaluation and certification frameworks (e.g., ClusterMax, NVIDIA Cloud validation) and apply that knowledge to shape our product and differentiation strategy. - Feedback to Product: Synthesize customer and competitive insights into clear requirements, priorities, and recommendations for the Product and Engineering teams. - Ecosystem Collaboration: Partner with GPU and AI ecosystem vendors (e.g., NVIDIA, AMD) to ensure alignment with performance, interoperability, and validation standards. - PoC Support: Collaborate with FAEs and Solution Engineers during customer PoCs to gather structured feedback and ensure successful deployment outcomes. - Thought Leadership: Act as a subject matter expert on AI/GPU cloud market dynamics and communicate insights through internal briefings, product planning sessions, and executive updates. Qualifications - 5–10 years of experience in solutions engineering, technical product management, competitive analysis, or product strategy, ideally in GPU computing, cloud infrastructure, or AI/ML systems. - Strong understanding of GPU cloud evaluation frameworks, NVIDIA Cloud validation programs, or similar benchmarking processes used by analysts and hardware partners. - Proven ability to translate complex customer and market insights into actionable product direction. - Technical background in Kubernetes, GPU orchestration, AI/ML workloads, or data center infrastructure. - Excellent communication and presentation skills; able to interface effectively with both engineers and executives. - Bachelor’s or higher degree in Computer Science, Physics, Engineering, or related technical discipline. COMPENSATION - We provide Competitive salary and equity based on your experience and skillset; - This is a Hybrid role - 3 days in office, 2 days WFH; Must locate in Palo Alto - Applicants must be authorized to work in the United States without need for visa sponsorship.

Requirements

Must-haves

Customer Engagement: Work directly with enterprise customers, AI developers, and ecosystem partners to understand workload patterns, pain points, and technical requirements.
Competitive and Market Analysis: Continuously track and analyze GPU cloud competitors (e.g., CoreWeave, Lambda, RunPod, AWS, Azure, GCP) across performance, cost, scalability, and customer experience.
Framework Insight: Maintain deep understanding of industry evaluation and certification frameworks (e.g., ClusterMax, NVIDIA Cloud validation) and apply that knowledge to shape our product and differentiation strategy.
Feedback to Product: Synthesize customer and competitive insights into clear requirements, priorities, and recommendations for the Product and Engineering teams.
Ecosystem Collaboration: Partner with GPU and AI ecosystem vendors (e.g., NVIDIA, AMD) to ensure alignment with performance, interoperability, and validation standards.
PoC Support: Collaborate with FAEs and Solution Engineers during customer PoCs to gather structured feedback and ensure successful deployment outcomes.
Thought Leadership: Act as a subject matter expert on AI/GPU cloud market dynamics and communicate insights through internal briefings, product planning sessions, and executive updates.
5–10 years of experience in solutions engineering, technical product management, competitive analysis, or product strategy, ideally in GPU computing, cloud infrastructure, or AI/ML systems.
Strong understanding of GPU cloud evaluation frameworks, NVIDIA Cloud validation programs, or similar benchmarking processes used by analysts and hardware partners.
Proven ability to translate complex customer and market insights into actionable product direction.
Technical background in Kubernetes, GPU orchestration, AI/ML workloads, or data center infrastructure.
Excellent communication and presentation skills; able to interface effectively with both engineers and executives.
Bachelor’s or higher degree in Computer Science, Physics, Engineering, or related technical discipline.

Nice-to-haves

None flagged.

Application prep

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Keywords to mirror

aigoawsazuregcpmlkubernetes

Platform: ashby
Effort: quick