Founding Account Executive, AI Data & Evaluation

Early-stage AI data infrastructure company · Remote anywhere in the US, with hubs in San Francisco and New York · Reports to the Founder & CEO

The opportunity

Our client is a growing data company that powers how artificial intelligence is trained and measured. They combine a software platform for building AI evaluations with a network of more than 25,000 credentialed experts, including physicians, surgeons, life sciences PhDs, and cybersecurity specialists. Together, these tell AI teams whether their models and agents actually perform like experts. You will own commercial relationships with frontier research labs and applied AI teams across healthcare, robotics, and language model development. In practice that means finding the specific researchers and data leads inside those organizations who have a reasoning gap they cannot close internally, understanding that gap precisely, and structuring an engagement that solves it.
 

In about 12 months, the company has:

• Closed three enterprise deals, including a master services agreement with one of the largest AI data companies
• Delivered evaluation work for a leading frontier AI lab
• Supported a major open-source cybersecurity benchmark funded by frontier lab grants
• Built a pipeline that includes frontier lab opportunities that could exceed $5M a year
• Started a distribution pilot with one of the world’s leading AI compute companies
• Reached a valuation of about $40M, with a $4M seed round committed and backing from one of Australia’s largest family offices

The company plans to hire four to five Account Executives over the next six months. This is one of the first seats.

The founder and team

The CEO is a former Vice President at one of the most recognized robotics companies in the world. He started this company as an expert research platform for investors. When he saw that the same experts were exactly what AI teams needed to evaluate their models, he moved the business toward AI and built the expert network to more than 25,000 people.

The team is small and senior. It includes an implementation lead and a first sales executive, both from the best-known company in AI training data, plus a computer science graduate who supports technical scoping and a part-time PhD researcher in frontier AI from a leading research university. The founder’s stated goal is to build a large, independent public company.

What you’ll sell

You’ll sell a combination of software and expertise:

• The platform: software for data annotation and for designing tasks that evaluate AI agents. It can be used as-is or custom-built to sit inside a customer’s existing systems.
• The expert network: credentialed specialists who create and complete annotation and evaluation work inside the platform.

The fastest-growing offering is end-to-end task creation in life sciences. Experts build complete evaluation tasks from scratch, so customers don’t need to supply raw data.

Your buyers are frontier AI labs and large enterprises: pharma companies building their own AI models, hyperscalers, and organizations with 2,000+ employees that need to measure how their AI performs. Depending on your background, you may focus on labs, enterprise and life sciences, or both.

The company wins on two things. It verifies expert credentials in regulated fields like medicine, where an unqualified annotator is a serious problem. It also moves fast, standing up an environment and delivering initial work within about seven days.

What winning looks like

• By week 3: you’re in conversations with potential buyers in your target accounts.
• By month 3: you’ve scoped a deal and it’s in the process of closing.
• By month 6: you’ve closed an enterprise deal.
• Over time: you’ve built a repeatable sales motion, and you grow into a larger role as the team scales.

What you’ll own

This role is entirely new business. You’ll own the full cycle, which typically runs three to six months or more:

• Pipeline: open conversations with the researchers, data leads, and AI leaders who own evaluation inside your target accounts.
• Technical discovery: learn how a customer evaluates its agents today, which vendors it uses and where they fall short, and how the company could fit into its existing setup.
• Scoping and pilots: work with the team to turn discovery into a demo environment or expert shortlist within days, write the scope of work with the customer, and run a paid pilot of a few weeks.
• Closing: convert pilots into enterprise agreements, and lead pricing and deal structure.
• Market intelligence: bring what buyers are asking for back to the founder, so it shapes what gets built.
• The playbook: help create the sales motion as one of the company’s first sellers.

What you bring

• Relationships with buyers who matter here. You can name the people you’d call first at frontier labs, pharma companies, hyperscalers, or other large enterprises, based on deals you’ve worked on before.
• A record of selling data products. You’ve personally closed enterprise deals for data, annotation, evaluation, data licensing, or closely related technical products.
• Technical fluency. You can run discovery with technical buyers and hold a substantive conversation about how AI models are evaluated, often without a solutions engineer in the room.
• Entrepreneurial drive. You’re comfortable with ambiguity, and you build what’s missing instead of waiting for it. You’ve likely done this at an early-stage company before.
• Low ego. You work collaboratively and add to the culture of a small team.

Helpful, not required

• Healthcare or life sciences sales experience, which is the company’s strongest market today
• Relationships with research or data teams at frontier AI labs
• Enterprise data deals with hyperscalers
• Experience as one of the first commercial hires at a seed or Series A company

If you haven’t sold into AI labs but have strong relationships with large enterprises and a history of selling technical data products, we’d still like to talk.