Staff Product Manager (Vmetal)
Jobgether
This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Staff Product Manager (vMetal) based in Canada.As a Staff Product Manager, you will shape the evolution of a bare-metal infrastructure platform designed for AI cloud providers and hyperscalers.You will own key product capabilities across hardware provisioning, lifecycle management, and high-performance networking.Working closely with product and engineering leadership, you will translate complex infrastructure requirements into clear product priorities and technical specifications.You will help define how physical computing resources are transformed into programmable, scalable environments for tenant workloads.Through hands-on validation and direct engagement with infrastructure experts, you will ensure the platform addresses real-world operational challenges.This role offers the opportunity to influence the future of AI infrastructure within a fast-growing, remote-first technology company.Accountabilities
In this role, you will drive product strategy and execution for the vMetal platform, with a particular focus on infrastructure provisioning and networking capabilities. You will work closely with engineering leaders, customers, and cross-functional teams to turn complex technical challenges into scalable product solutions. Your responsibilities will include:Define product priorities and technical direction across compute and networking capabilities, aligning business objectives with engineering execution.Own the platform's networking layer, including the provisioning and isolation of tenant networks across InfiniBand and high-speed Ethernet fabrics.Define how networking capabilities support tenant virtual private clouds, rail-optimized GPU fabrics, fabric controllers, and NVIDIA networking technologies.Translate infrastructure requirements and strategic priorities into detailed product specifications and actionable engineering plans.Partner directly with product and engineering leadership to shape the platform roadmap and guide important technical trade-offs.Personally test alpha and beta releases against physical bare-metal hardware and network fabrics, identifying integration issues before customer deployment.Engage with platform engineers, network engineers, and architects at AI cloud providers and hyperscalers to understand their infrastructure needs and operational challenges.Convert customer feedback and real-world technical issues into product requirements, improvements, and platform capabilities.Monitor developments across bare-metal infrastructure, GPU computing, and data center networking to identify market opportunities and emerging technologies.Develop and refine product positioning for technical buyers, ensuring alignment between engineering capabilities, sales messaging, and customer support.Collaborate across product, engineering, sales, and marketing teams to ensure successful product development and market adoption.Requirements
The ideal candidate brings deep technical knowledge of cloud infrastructure, networking, or data center systems, combined with the ability to influence product direction and make informed technical decisions. A traditional product management background is not essential;
candidates with relevant experience in networking, hardware, or infrastructure technology are also encouraged to apply. Key qualifications include:At least 5 years of experience in cloud infrastructure, data center networking, bare-metal systems, or GPU/HPC platforms.Strong understanding of networking technologies, including InfiniBand, VLAN, VXLAN, EVPN, and BGP.Familiarity with NVIDIA's networking ecosystem, including Spectrum and Quantum switches, UFM, Cumulus Linux, and NVUE.Solid understanding of bare-metal provisioning, out-of-band server management technologies such as Redfish and IPMI, and PXE boot processes.Ability to make informed product and technical trade-offs based on a strong understanding of infrastructure architecture and networking systems.Experience engaging directly with platform engineers, network engineers, and infrastructure architects.Strong communication and collaboration skills, with the ability to translate complex technical concepts into clear product requirements and strategic recommendations.Ability to work effectively with engineering and leadership teams to prioritize initiatives and guide product development.Additional qualifications considered an advantage
Familiarity with AI networking architectures designed for GPU training and inference workloads, including RoCEv2, rail-optimized topologies, and Spectrum-X.Experience building or managing Kubernetes-as-a-Service (KaaS) offerings at a cloud provider, technology vendor, or large internal platform team.Experience working in a startup environment, with the adaptability to navigate rapid growth, changing priorities, and evolving business needs.Benefits
Competitive compensation package, including equity.Health, dental, vision, and life insurance coverage for employees and eligible dependents, with benefits varying by country.Flexible working schedule, with an emphasis on results and outcomes rather than fixed working hours.Fully remote working environment, with flexibility regarding where you work.Supportive, distributed team culture that encourages collaboration, ownership, and continuous learning.Opportunity to contribute to cutting-edge AI infrastructure and open-source technology.Exposure to complex technical challenges involving hyperscale infrastructure, GPU platforms, and high-performance networking.Opportunity to influence product strategy and help establish new standards in AI infrastructure.
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In this role, you will drive product strategy and execution for the vMetal platform, with a particular focus on infrastructure provisioning and networking capabilities. You will work closely with engineering leaders, customers, and cross-functional teams to turn complex technical challenges into scalable product solutions. Your responsibilities will include:Define product priorities and technical direction across compute and networking capabilities, aligning business objectives with engineering execution.Own the platform's networking layer, including the provisioning and isolation of tenant networks across InfiniBand and high-speed Ethernet fabrics.Define how networking capabilities support tenant virtual private clouds, rail-optimized GPU fabrics, fabric controllers, and NVIDIA networking technologies.Translate infrastructure requirements and strategic priorities into detailed product specifications and actionable engineering plans.Partner directly with product and engineering leadership to shape the platform roadmap and guide important technical trade-offs.Personally test alpha and beta releases against physical bare-metal hardware and network fabrics, identifying integration issues before customer deployment.Engage with platform engineers, network engineers, and architects at AI cloud providers and hyperscalers to understand their infrastructure needs and operational challenges.Convert customer feedback and real-world technical issues into product requirements, improvements, and platform capabilities.Monitor developments across bare-metal infrastructure, GPU computing, and data center networking to identify market opportunities and emerging technologies.Develop and refine product positioning for technical buyers, ensuring alignment between engineering capabilities, sales messaging, and customer support.Collaborate across product, engineering, sales, and marketing teams to ensure successful product development and market adoption.Requirements
The ideal candidate brings deep technical knowledge of cloud infrastructure, networking, or data center systems, combined with the ability to influence product direction and make informed technical decisions. A traditional product management background is not essential;
candidates with relevant experience in networking, hardware, or infrastructure technology are also encouraged to apply. Key qualifications include:At least 5 years of experience in cloud infrastructure, data center networking, bare-metal systems, or GPU/HPC platforms.Strong understanding of networking technologies, including InfiniBand, VLAN, VXLAN, EVPN, and BGP.Familiarity with NVIDIA's networking ecosystem, including Spectrum and Quantum switches, UFM, Cumulus Linux, and NVUE.Solid understanding of bare-metal provisioning, out-of-band server management technologies such as Redfish and IPMI, and PXE boot processes.Ability to make informed product and technical trade-offs based on a strong understanding of infrastructure architecture and networking systems.Experience engaging directly with platform engineers, network engineers, and infrastructure architects.Strong communication and collaboration skills, with the ability to translate complex technical concepts into clear product requirements and strategic recommendations.Ability to work effectively with engineering and leadership teams to prioritize initiatives and guide product development.Additional qualifications considered an advantage
Familiarity with AI networking architectures designed for GPU training and inference workloads, including RoCEv2, rail-optimized topologies, and Spectrum-X.Experience building or managing Kubernetes-as-a-Service (KaaS) offerings at a cloud provider, technology vendor, or large internal platform team.Experience working in a startup environment, with the adaptability to navigate rapid growth, changing priorities, and evolving business needs.Benefits
Competitive compensation package, including equity.Health, dental, vision, and life insurance coverage for employees and eligible dependents, with benefits varying by country.Flexible working schedule, with an emphasis on results and outcomes rather than fixed working hours.Fully remote working environment, with flexibility regarding where you work.Supportive, distributed team culture that encourages collaboration, ownership, and continuous learning.Opportunity to contribute to cutting-edge AI infrastructure and open-source technology.Exposure to complex technical challenges involving hyperscale infrastructure, GPU platforms, and high-performance networking.Opportunity to influence product strategy and help establish new standards in AI infrastructure.
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