About the job
Join Rockstar as we revolutionize the AI infrastructure landscape! We are building the foundational AI backbone for the next wave of intelligent products, enabling fast-growing AI startups to design, fine-tune, evaluate, deploy, and maintain specialized models across text, vision, and embeddings. Think of us as the 'AWS for AI models', a comprehensive backend for fine-tuning, reinforcement learning, inference, and model maintenance. Our clientele consists of Series A–C AI companies developing enterprise-grade products, with a straightforward promise: enhancing your AI systems.
We are seeking a Founding Go-To-Market Lead to spearhead our initial GTM strategy from the ground up, encompassing content creation, event management, partnership development, customer engagement, and product strategy. This position offers a unique opportunity to immerse yourself in a technically advanced product while influencing the commercial roadmap from inception.
Why This Role is Crucial
The current AI infrastructure is disjointed and primarily designed for researchers rather than product teams. Our mission is to change that. As our first GTM hire, you'll have the chance to delineate the market sectors we engage in, formulate compelling narratives that can shift market perceptions, and construct a robust top-of-funnel engine for the company. Collaborating directly with the founders, you will help shape product direction, pricing strategies, ideal customer profile evolution, and partnerships within the ecosystem (such as with GPUs, model vendors, and frameworks).
This is a builder role ideal for an individual passionate about being at the crossroads of engineering, product development, community engagement, and commercialization.
Key Responsibilities
Execution (0→1 GTM Buildout)
• Drive top-of-funnel growth by identifying, qualifying, and nurturing early customer segments, including Series A–C AI startups, infrastructure-heavy teams, and enterprise ML teams.
• Produce compelling technical content: create in-depth case studies, benchmarks, architecture articles, and thought leadership pieces that resonate with technical founders and ML engineers.
• Enhance event and community presence: participate in, and speak at, AI meetups, infrastructure conferences, and ecosystem events; represent the company with charisma and technical credibility.
• Manage GPU and ecosystem partnerships: work closely with GPU providers, cloud partners, and model ecosystem vendors to foster co-marketing and co-selling initiatives.
• Connect product and customer needs: gain an in-depth understanding of the company's capabilities and assist prospects in aligning their infrastructure with their model strategies (fine-tuning to reinforcement learning to pre-training).
Strategy (Shaping the Company)
• Establish pricing and packaging strategies for model-centric customers through fine-tuning, reinforcement learning workflows, inference, maintenance, evaluation, and platform usage.
• Expand the ideal customer profile over time by identifying adjacent customer segments and guiding the upmarket movement.
• Influence the product roadmap by helping prioritize both horizontal (modalities, pipelines) and vertical (evaluations, agents, monitoring) expansions.
• Craft a compelling category narrative: assist in defining the market position and storytelling that resonates with customers and partners.
