Account Executive

Founding Account Executive

Early-stage AI data infrastructure company

Hybrid in San Francisco or New York, or remote anywhere in the US

The opportunity

Our client is a growing data company that powers how artificial intelligence is trained and measured. They build advanced data infrastructure and evaluation frameworks from proprietary, expert-generated data. Their customers are three groups working at frontier: AI labs, companies building autonomous AI agents, and institutional investors backing the technology.

Their edge is the source of the data. The company captures structured reasoning from credentialed experts, including physicians from a top-ranked academic medical center and senior leaders from some of the most respected companies in technology. It turns that reasoning into training data, benchmarks, and evaluations that show whether a model actually thinks like an expert. One expert pool generates both the training data and the tests, and every judgment traces back to a named reviewer. For customers making high stakes decisions about AI, that rigor is the product.

They are pre-seed, but the platform is live and demand is growing. The company is now bringing on an Account Executive to turn that momentum into lasting enterprise relationships, and to help build the sales motion that defines its next stage.

The product is live, the team is five people, and its leaders come from top AI data, autonomy, and technology companies Scale AI, Amazon, Uber ect. This role is one of the first sellers on the team and works directly with the CEO.

The CEO is a former Vice President at one of the most recognized robotics companies in the world. There, he helped scale autonomous systems from ambitious idea to real-world operation. He has spent his career where hard technology meets commercial execution. He knows what it takes to move a technical product from promising to indispensable.

He moves fast, makes decisions directly, and wants sellers who will shape the business, not just carry a number. You'll work directly with him. Your insight from the field will change what gets built, how it's priced, and where the company goes next.

What winning looks like

• By month six, you've closed an enterprise deal.
• By day 90 you have conversations progressing.
• Over time, you've created a repeatable sales motion and playbook, and you've grown into a larger role as the team expands.

What you'll own

• You'll build and own the account plan for a defined set of labs and applied AI teams across multiple domains, including who the real buyers are, what their current evaluation and post-training bottlenecks look like, and where expert reasoning data changes their results.
• Technical discovery. You'll lead substantive conversations with research and data leaders. You'll turn what you learn into precise requirements the team can build against.
• Deal design. You'll structure and negotiate enterprise engagements, environment builds, licensing arrangements, and data agreements. You'll own pricing strategy and deal shape.
• Market intelligence. You'll bring competitive and demand intelligence back into the company, so that the roadmap reflects what labs are actually asking for rather than what we assume they want.
• Expert credibility. Work alongside their expert network so that the technical experts backing a proposal are credible to a technical buyer.

The playbook. You'll create the sales motion from the ground up. There is no playbook here yet, and you will be the person who has real input into how that's formed.

What you bring

• 3+ years selling technical products to technical buyers, with clear ownership of complex enterprise deals. Deals of $500K or more are ideal.
• Direct experience selling to or working inside one of these: AI labs, robotics or autonomy companies, data infrastructure companies, or research organizations. Technical data selling knowledge is a must.
• Enough fluency in how modern models are trained and evaluated to discuss post-training, evaluation design, and reward signals without a solutions engineer.
• A track record of closing without a big company brand, an SDR team, or heavy enablement behind you.
• Comfort with ambiguity at a company where the product is still taking shape and your input changes what gets built.

Helpful, not required

• Relationships with research or data teams at frontier labs
• Experience in healthcare, life sciences, clinical operations, or other regulated environments
• Data or evaluation experience in robotics, autonomy, or embodied AI
• A prior role as one of the first commercial hires at a seed or Series A company

DOE comp: 160-200k base, x2 OTE, uncapped