About The Position

As our GTM Director, you will bridge the gap between our hardware architecture and the customer’s model training/inference requirements. You will not just sell servers; you will sell a performance platform, requiring deep technical fluency to prove TCO advantages and software compatibility. This is a high-impact, customer-facing role that blends storytelling, technical fluency, and deal-making.

Requirements

  • 10+ years in technical sales, BD, or GTM, with proven success selling compute infrastructure, semiconductors, or cloud platforms.
  • Experience navigating conversations with AI researchers and infrastructure engineers regarding memory bandwidth, interconnects, and LLM model architectures.
  • Demonstrated ability to position hardware solutions in a market dominated by incumbents.
  • Ability to define sales playbooks, pricing models, and GTM strategies from 0 to 1.

Nice To Haves

  • Experience in early-stage startups or launching new GTM initiatives

Responsibilities

  • Drive Design Wins: Own the full sales lifecycle, including technical validation (benchmarking inference throughput, latency, and power efficiency) vs. incumbents (e.g., NVIDIA, specialized ASICs).
  • Negotiate complex contracts and navigate procurement processes with large organizations.
  • Quantify TCO Advantage: Develop models to articulate the Total Cost of Ownership (TCO) advantage of our platform against current datacenter standard racks, focusing on energy per token and rack density.
  • Ecosystem & Software Evangelism: Partner with our software engineering teams to articulate the value of our software architecture. Evangelize compatibility with common developer frameworks/APIs and ensure customers understand the development ease of use.
  • Strategic Partnerships: Build deep ties with key customers including hyperscaler procurement teams, datacenter operators, and CTOs of AI-frontier labs.
  • Pipeline Generation: Lead outbound efforts targeting technical teams at companies specializing in the future of inference (e.g., LLM labs, code development, and quantitative trading firms).
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