Senior Product Manager, AI Infrastructure

Who We Are Vultr is on a mission to make high-performance cloud infrastructure easy to use, affordable, and locally accessible for enterprises and AI innovators around the world. With 33 global cloud data center locations, Vultr is trusted by hundreds of thousands of active customers across 185 countries for its flexible, scalable, global Cloud Compute, Cloud GPU, Bare Metal, and Cloud Storage solutions. In December 2024 Vultr announced an equity financing at a $3.5 billion valuation. Founded by David Aninowsky and self-funded for over a decade, Vultr has grown to become the world’s largest privately-held cloud infrastructure company. Vultr Cares 100% company-paid insurance premiums for employee medical, dental and vision plans. 401(k) plan that matches 100% up to 4%, with immediate vesting Professional Development Reimbursement of $2,500 each year 11 Holidays + Paid Time Off Accrual + Rollover Plan Commitment matters to Vultr! Increased PTO at 3 year and 10 year anniversary + 1 month paid sabbatical every 5 years + Anniversary Bonus each year $500 stipend for remote office setup in first year + $400 each following year Internet reimbursement up to $75 per month Gym membership reimbursement up to $50 per month Company paid Wellable subscription Join Vultr Vultr is seeking a Senior Product Manager, AI Infrastructure to work directly with customers and engineering teams to define, build, and deliver AI infrastructure capabilities for large-scale GPU workloads. The ideal candidate deeply understands customer requirements across AI infrastructure and can translate them into clear product and engineering requirements, with strong technical depth across GPU compute, storage, networking, cluster orchestration, and AI workload infrastructure. This is your opportunity to join our fast growing team and leave your mark on Vultr and the future of Cloud Infrastructure. Key Responsibilities Own the discovery and definition of customer requirements for AI infrastructure use cases, including training, inference, GPU clusters, bare metal, managed orchestration, networking, and storage Work directly with strategic customers to understand their technical needs, deployment timelines, workload patterns, and success criteria Translate customer requirements into clear product requirements, technical specifications, and engineering priorities Partner closely with engineering, infrastructure, networking, storage, and operations teams to deliver customer-ready solutions Drive alignment across customer needs, product roadmap, architecture decisions, and delivery execution Understand and define requirements across GPU compute, CPU, memory, local and shared storage, high-performance networking, cluster topology, and orchestration layers such as Kubernetes and Slurm Support customer conversations around infrastructure design, capacity planning, performance expectations, operational readiness, and acceptance criteria Help define product capabilities that can scale beyond a single customer into repeatable AI infrastructure offerings Qualifications 5+ years of experience in technical product management, with focus on infrastructure, cloud computing, or AI/ML platforms Deep technical understanding of GPU compute, high-performance networking (InfiniBand, RoCE), distributed storage, and cluster orchestration (Kubernetes, Slurm) Experience working directly with enterprise customers to define infrastructure requirements and translate them into product specifications Strong understanding of AI/ML workloads including training, fine-tuning, and inference at scale Proven ability to collaborate with engineering teams to deliver complex infrastructure products Excellent written and verbal communication skills, with the ability to engage both technical and executive audiences Experience with bare metal infrastructure and managed cloud services Bachelor's degree in Computer Science, Engineering, or related technical field; advanced degree preferred Compensation $130,000 - $165,000 Final compensation will vary depending on years of experience, background/skill set, location, and applicable laws. 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