Senior Al Product Director

Tensordyne is an AI system solution company building very high-performance, low-power generative AI inference systems. Our mission is to enable multimodal Generative AI inference acceleration at scale through custom silicon, hardware, and software for hyperscaler and neocloud data center customers. We are a well-funded, fast-paced startup with headquarters in Sunnyvale, CA, and Munich, Germany, and remote team members across North America and Europe.

About the role

We're looking for an experienced (Sr.) Director of Technical Product Management who is passionate and deeply knowledgeable about AI inference compute in datacenters, across the entire stack (silicon, hardware, and software). Reporting to the VP of product management, you will help focus AI compute product efforts that define the future of inference at Tensordyne’s customers.

Responsibilities

• Lead the definition of Tensordyne's next generation of AI inference compute products, with an innovative yet pragmatic and well-communicated technology roadmap, shaping the company's GTM strategy.
• Engage with external technology partners, customers, AI industry researchers, and internal engineering & business stakeholders to coalesce insights and requirements into winning AI product plans and strategies.
• Research, define, and drive essential competitive analysis, key metrics tracking, cost modeling, customer demos, and product release schedules to ensure Tensordyne's superiority to alternative solutions.
• Oversee and ensure the success of key customers' projects, anticipating their software and hardware needs while reacting to pertinent feedback.
• Work hand-in-hand with marketing to design campaigns promoting Tensordyne's AI technology and products, demonstrating thought leadership.
• Serve as an occasional external spokesperson (e.g., at conferences).

Qualifications

Technical

• Deep understanding of the execution flow of modern AI inference systems, particularly large-scale Mixture-of-Experts (MoE) models and world models.
• Strong knowledge of AI inference architectures, including:
  • Key-Value (KV) cache management and optimization
  • AI inference server architectures
  • Multi-user and multi-agent inference scheduling
  • Parallelization techniques (tensor, pipeline, expert, and data parallelism)
  • Compute disaggregation and resource orchestration
  • Modern AI inference system KPIs, performance metrics, Pareto optimization, and efficiency trade-offs
  • Prefill vs. Decode design trade-offs (from silicon to business model)
• Comprehensive understanding of AI compute infrastructure, including:
  • Silicon architectures and accelerator technologies
  • Hardware performance characteristics and architectural trade-offs
  • System architecture and rack-scale design
  • High-performance networking topologies
  • Optical interconnects and next-generation data center infrastructure
• Strong understanding of AI software stacks, including AI model compilers, runtime environments, and inference optimization frameworks.
• Demonstrated ability to connect low-level hardware capabilities with system-level performance and customer business outcomes.

Business & Commercial Acumen

• Strong techno-economic understanding of AI compute platforms, including:
  • Cost-performance optimization
  • Infrastructure Total Cost of Ownership (TCO)
  • Performance-per-dollar analysis
  • Energy efficiency and utilization metrics
  • Business models supporting large-scale AI inference deployments
• Ability to translate complex technical concepts into compelling customer value propositions.
• Understanding of commercial drivers influencing enterprise AI infrastructure purchasing decisions.

Product Management & Strategic Skills

• Proven ability to define and execute product strategy for complex technical products.
• Experience developing product roadmaps informed by customer requirements, competitive analysis, and technology trends.
• Strong systems-thinking approach with the ability to evaluate trade-offs across hardware, software, infrastructure, performance, and economics.
• Highly structured and organized approach to product planning, prioritization, execution, and cross-functional coordination.
• Experience managing highly technical products throughout the product lifecycle.

BS or MS degree in Computer Science, Computer Engineering, or a similar field.

Benefits

We take care of our people and their families with comprehensive benefits, competitive compensation, flexible spending options, and recognition programs.

Culture

• Put people first. We only succeed when our people succeed.
• Ethics and integrity always; being open, honest, and respectful of everyone.
• Think Big. Be ambitious and have audacious goals of global scale.
• Aim for excellence. Quality and excellence count in everything we do.
• Own it and get it done. Results matter!
• Make each person better together than they would be as an individual.
• Embrace each other's differences, and embrace that there will be differences.