GTM, Embodied AI
About the position
Niantic Spatial is building the future of physical AI with groundbreaking mapping technology that unlocks a new dimension of interaction and spatial intelligence. Their reconstruction technology captures environments with geometric accuracy and extreme detail from any standard camera, and their Visual Positioning System delivers precise positioning almost anywhere in the world. They serve customers across robotics, the public sector, and energy and industrial markets. This role is for an entrepreneurial Go-to-Market lead to build pipeline and customer relationships within the Embodied AI group, focusing on overcoming the sim-to-real gap for visual-spatial understanding. The lead will work directly alongside the group's General Manager, mapping the market, opening doors, and closing business in step with product development. This role offers significant independence, direct access to product developers, and real responsibility for business success. It is for individuals who are natural-born sellers, energized by customer interaction, knowledgeable in the robotics ecosystem, and relentless in pursuing opportunities. This is not a role for someone who needs inbound leads, a finished playbook, or a fully baked product; it requires a passion for building, finding use cases, earning customer conviction, and closing deals. The role will initially focus on accountability for qualified pipeline, customer learning, and deliverable business, rather than a sales quota.
Responsibilities
- Map the Market - Build and maintain a comprehensive view of prospects, their use cases, and the right contacts. Track funding, hiring, launches, and deployments, and hold a point of view on who we should pursue, why, and when.
- Open Doors - Build qualified pipeline through relationships, targeted outreach, introductions, and events. Get into the communities where customers spend time, and turn approaches that earn attention into repeatable ones.
- Qualify and Learn - Immerse in customers' workflows: what they're trying to do, what they've tried, where it breaks, and what that costs them. Establish fit, urgency, and how a buying decision will happen, and bring candid input on product-market alignment back to the General Manager and Product leader.
- Develop Relationships - Be useful to accounts not yet ready to be served. Work with Marketing on insights, introductions, content, and events, and know what needs to change in their business or our capabilities for an opportunity to become actionable.
- Close Business - Run opportunities through evaluation, proposal, negotiation, and signature. Agree what an evaluation must prove, who will decide, and what follows success. Prepare colleagues properly and stay engaged through handoff so commitments are delivered.
- Shape the Commercial Model - Help design commercial models for a maturing product, finding simple solutions where the path isn't laid out, and bringing discipline to how early deals are structured.
Requirements
- Relationships that open doors. You already know founders, engineering leaders, or buyers in robotics, embodied AI, or the infrastructure and tooling companies serving them, and you have a track record of building new relationships beyond your existing network.
- Experience personally winning early customers for a technical product. You sourced opportunities and closed business while the use case, buyer, or commercial approach was still being worked out, and you can explain what you did to make it happen.
- Experience shaping the deal itself. You've worked with founders or technical teams to turn a customer problem into a concrete offer covering scope, proof of value, commercial terms, and a path from evaluation to paid adoption, and you've secured commitments of budget and engineering time.
- Evidence that you changed the approach because of what you learned. You can point to customer evidence that changed who your team targeted, what it offered, or how it sold, and explain what happened next.
- Credibility with technical buyers. You've sold to engineering or research teams and can hold a substantive conversation about their workflows, including the roles of simulation, training data, and evaluation in embodied AI, and concepts such as reinforcement learning, imitation learning, and sim-to-real transfer.
- A bachelor's degree in a relevant field, or equivalent experience.
Nice-to-haves
- You've turned initial pilots into sustained usage, renewals, or expansion.
- You've helped turn a handful of early wins into a repeatable approach across customers.
- You've partnered with or sold within the NVIDIA robotics ecosystem.
- You've sold into defense or industrial robotics teams.
Benefits
- medical, dental, and vision coverage
- 401(k)
