Senior Technical Product Marketing Manager

This is a fully remote position, open to applicants in Kazakhstan, +1 more country.

📋 Description

• Create white papers, technical blogs, architecture decision guides, and materials for NVIDIA certifications (NCP, NCX).

• Develop and manage the technical demo portfolio, which includes live demonstrations, recorded walkthroughs, and supportive lab environments that cover bare-metal provisioning, GPU cluster handoff, and AI workload deployment.

• Conduct technical competitive analysis, including hands-on assessments of rival platforms and emerging neocloud control planes.

• Convert engineering and field data into robust technical claims regarding cluster turn-up time, provisioning success rates at node scale, NCCL and fabric benchmark outcomes, GPU utilization and allocation efficiency, failure-domain behavior, and multi-tenant isolation.

• Interact directly with customers and prospects through technical deep dives and architecture reviews, in collaboration with sales engineering and solution architects.

• Equip sales engineering and solution architects with POC success criteria, testing plans, discovery guides, and sizing and TCO models.

• Assist with analyst and technical media briefings and deliver presentations at conferences such as KubeCon, NVIDIA GTC, and RAISE.

• Provide structured roadmap insights to product management based on POC patterns, recurring technical objections, and competitive loss evaluations.

• Transform customer and engineering insights into technically sound content and feedback for product management.

• Validate product assertions in the lab prior to customer delivery, ensuring accurate representation of current capabilities and constraints.

⛳️ Requirements

• Over 6 years of experience in technical product marketing, technical marketing engineering, solutions architecture, or infrastructure engineering, with a focus on externally facing technical content.

• Proficient in Kubernetes, including cluster operations, CRDs and controllers, and troubleshooting.

• Extensive knowledge of bare-metal and accelerated infrastructure, covering server provisioning and lifecycle, InfiniBand and RoCE fabrics, GPU node provisioning and health, NVIDIA GPU Operator and MIG, DPUs, and data center power and cooling limitations.

• Familiarity with the AI infrastructure stack, encompassing inference serving (e.g., vLLM, TensorRT-LLM, NIM), training and scheduling (e.g., Slurm, Soperator), and MLOps tools (e.g., Kubeflow, Ray).

• Experience in presenting to and addressing inquiries from infrastructure architects and technical purchasers.

• A portfolio of published technical writing, including white papers or technical blogs.

• Willingness to travel for customer interactions and industry events.

• A keen interest in understanding AI infrastructure.

• Strong collaborative skills to work effectively with engineers, product managers, and executives.

• Ability to manage multiple projects and meet deadlines.

• A passion for developer communities and the cloud-native ecosystem.

• A tendency to prioritize the delivery of content and rapid iteration.

• Nice to have: Experience in GPU-as-a-service, neocloud, HPC, or hyperscaler infrastructure.

• Nice to have: Direct experience with NVIDIA ecosystems, including NCP and NCX certification programs, DGX/HGX and GB200/GB300 NVL-class systems, BlueField DPUs, and Spectrum-X or Quantum fabrics.

• Nice to have: Familiarity with Cluster API, bare metal provisioning, k0s, k3s, Talos, or similar cluster lifecycle tools.

• Nice to have: Exposure to sovereign AI, regulated industry, or public-sector infrastructure procurement.

• Nice to have: A record of accepted conference presentations or a collection of published technical writing.

🏝️ Benefits

• Work within some of the most advanced AI infrastructure environments currently in production.

• Engage with the latest NVIDIA GPU technologies, Kubernetes platforms, and high-performance networking environments.

• Contribute to the establishment of operational standards and reliability practices for next-generation AI infrastructure services.

• Influence the adoption of AI-driven operational capabilities through k0rdent AI.

• Collaborate with highly skilled engineers tackling complex infrastructure and platform challenges at scale.

• Become part of a growing organization that is heavily investing in AI infrastructure, platform services, and operational innovation.

• Enjoy the flexibility of remote work.