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Tensordyne is an AI systems company building high-performance, low-power generative AI inference systems using custom silicon, hardware, and software. The company serves hyperscaler and neocloud data center customers with multimodal AI inference acceleration solutions. Headquartered in Sunnyvale, CA with offices in Munich, Germany, and distributed teams across North America and Europe.
As Senior Director of Technical Product Management, you will lead the definition and strategy of Tensordyne's next-generation AI inference compute products. Reporting to the VP of Product Management, you'll shape the company's go-to-market strategy and product roadmap across the full stack—from silicon through software.
Key responsibilities include:
• Defining Tensordyne's AI inference compute product strategy and technology roadmap with clear GTM alignment
• Engaging with technology partners, customers, AI researchers, and internal stakeholders to translate market insights into winning product plans
• Conducting competitive analysis, defining key metrics, cost modeling, customer demos, and release schedules to ensure competitive superiority
• Overseeing success of key customer projects, anticipating needs, and incorporating feedback into product development
• Collaborating with marketing to design campaigns that promote Tensordyne's technology and establish thought leadership
• Serving as occasional external spokesperson at industry conferences
You'll need deep technical understanding of modern AI inference systems, particularly large-scale Mixture-of-Experts (MoE) models and world models. Required expertise spans AI inference architectures (KV cache management, inference servers, scheduling, parallelization techniques, compute disaggregation), AI compute infrastructure (silicon architectures, hardware performance, system design, networking, optical interconnects), and AI software stacks (compilers, runtimes, optimization frameworks).
You should demonstrate ability to connect low-level hardware capabilities with system-level performance and customer business outcomes. Strong techno-economic understanding of AI compute platforms is essential, including cost-performance optimization and infrastructure TCO analysis.
The ideal candidate has years of engineering background enabling profound technical understanding across product dimensions, combined with product management experience, business development acumen, and excellent communication and networking skills. This is a self-starter role in a well-funded, fast-paced startup environment.
