Director of Product (Ecosystem)

Join SambaNova, a leading AI infrastructure company, as the Director of Product, Ecosystem. In this role, you will own the ecosystem strategy for our core products, define integration areas, and drive partner strategy. You will also represent SambaNova in community work, support co-engineering with model partners, and deliver a quarterly ecosystem scorecard to the executive team. This position requires 10+ years of experience in AI infrastructure, accelerators, or data center systems, with a focus on product management and ecosystem strategy.

• Définir et mettre en œuvre la stratégie d'écosystème pour les produits de SambaNova, y compris les intégrations à poursuivre et la manière de les positionner.
• Prendre des décisions concernant l'intégration de RDU à chaque couche, expédier les architectures de référence et les certifications.
• Établir la stratégie de partenariat et travailler en étroite collaboration avec les gestionnaires de produits de domaine et l'ingénierie.

• Fluency in inference economics: cost per million tokens, tokens per second per user, and latency and throughput tradeoffs by workload
• 10+ years in AI infrastructure, accelerators, or data center systems, including 8+ years in product management with direct ownership of ecosystem, platform, or partner-facing product
• Working fluency across scale-out networking, inference serving, storage and caching, prefill and decode disaggregation, CPU offload, and compiler toolchains, with depth in at least two
• Bachelor's degree in computer science, electrical engineering, or a related technical field, or equivalent experience
• Shipped partner-facing product artifacts (reference architectures, certification programs, or integration surfaces) that external teams adopted
• Comfortable owning a strategy that other organizations execute. Technical depth in both network fabric topologies and inference serving stacks
• Concise, quantified written communication for executive audiences
• Track record of converting partnerships into measurable deployments, demand, or revenue
• Experience at both a silicon or systems vendor (for example, the CUDA, ROCm, or oneAPI ecosystems, or an inference accelerator startup) and at a model lab or inference provider
• Has closed and delivered at least one co-optimization engagement with a model provider
• Contributions to, or close working relationships with, the vLLM, SGLang, llm-d, PyTorch, or MLIR communities
• Exposure to hardware sales cycles: racks, data center constraints (power, cooling, density), and financing-backed deals
• Has run joint go-to-market with networking, storage, or compute vendors that share a common buyer