Head of Frontier AI

<div class="content-intro"><h2><strong>About Invisible</strong></h2> <p>Invisible Technologies makes AI work. Our end-to-end AI platform structures messy data, automates digital workflows, deploys agentic solutions, measures outcomes, and integrates human expertise where it matters most.</p> <p>Our platform cleans, labels, and structures company data so it is ready for AI. It adapts models to each business and adds human expertise when needed, the same approach we have used to improve models for more than 80% of the world’s top AI companies, including Microsoft, AWS, and Cohere.</p> <p>Our successes span industries, from supply chain automation for Swiss Gear to AI-enabled naval simulations with SAIC, and validating NBA draft picks for the Charlotte Hornets.</p> <p>Profitable for more than half a decade, Invisible reached $134M in revenue and ranked as the number two fastest growing AI company on the 2024 Inc. 5000. In September 2025, we raised $100M in growth capital to accelerate our mission of making AI actually work in the enterprise and to advance our platform technology.</p></div><h2><strong>About the RL Data Lab</strong></h2> <p>Invisible's RL Data Lab builds the data and evaluation infrastructure that model builders use to train and measure their models, from foundation labs to large tech companies to enterprises building their own agentic systems. The Head of Frontier AI owns that transition across every customer that builds or adapts models: foundation labs today, and a growing set of tech companies and enterprises over time.</p> <h2><strong>The role</strong></h2> <p>You will own revenue growth from model builders, across foundation labs, large tech companies, and enterprises: expanding existing accounts, opening new ones, and adding new types of revenue on top of the services we sell today. This is a commercial leadership role with a product mandate. You will run these client relationships end to end, and you will be the voice of the customer inside Invisible, working with Product and Engineering to turn what labs need into offerings we can sell at scale.</p> <p>Your mandate has three parts:</p> <ul> <li><strong>Grow existing clients</strong> by expanding scope, deepening multi-threaded relationships, and moving accounts from one-off projects to recurring programs.</li> <li><strong>Win new clients</strong> across foundation labs, emerging frontier labs, large tech companies building genAI products, and enterprises training or fine-tuning models for agentic solutions.</li> <li><strong>Build new revenue lines</strong> by bringing newer offerings (staff aug, data brokerage, agentic trajectories) to market alongside our core RLHF and SFT work.</li> </ul> <h3><strong>Who you'll sell to</strong></h3> <table> <thead> <tr> <th> <p>Segment</p> </th> <th> <p>Who they are</p> </th> <th> <p>What they need from us</p> </th> </tr> </thead> <tbody> <tr> <td> <p>Foundation and frontier labs</p> </td> <td> <p>Labs training frontier models</p> </td> <td> <p>Post-training data, RL environments, agentic trajectories, specialist talent at scale</p> </td> </tr> <tr> <td> <p>Large tech companies</p> </td> <td> <p>Teams building genAI products and in-house models</p> </td> <td> <p>Domain-specific SFT/RLHF data, evals, embedded experts</p> </td> </tr> <tr> <td> <p>Enterprises</p> </td> <td> <p>Companies moving from buying AI to building or fine-tuning models for agentic workflows</p> </td> <td> <p>Proprietary-data fine-tuning, evaluation, trajectories for their own agents, staff aug</p> </td> </tr> </tbody> </table> <p>Labs are the core of the business today; tech companies and enterprises are where the next wave of model-building revenue will come from. Enterprise accounts are run in partnership with Enterprise GTM.</p> <h3><strong>What you'll sell</strong></h3> <p>You will sell a portfolio that spans our established services and the newer, more productized lines we are building.</p> <table> <thead> <tr> <th> <p>Offering</p> </th> <th> <p>What labs buy</p> </th> <th> <p>Where it is today</p> </th> </tr> </thead> <tbody> <tr> <td> <p>RL environments and long-horizon agentic trajectories</p> </td> <td> <p>Environments, tasks, graders, and multi-step agent trajectories for reinforcement learning</p> </td> <td> <p>Growth line; shaped closely with Product and Engineering</p> </td> </tr> <tr> <td> <p>RLHF / SFT</p> </td> <td> <p>Expert-generated preference data, demonstrations, and evaluations for post-training</p> </td> <td> <p>Core revenue; scale and margin expansion</p> </td> </tr> <tr> <td> <p>Staff augmentation</p> </td> <td> <p>Vetted domain experts and specialists embedded with lab teams on W-2 or 1099 terms</p> </td> <td> <p>New business unit; first deals and repeatable motion</p> </td> </tr> <tr> <td> <p>Data brokerage</p> </td> <td> <p>Licensed and sourced datasets matched to lab training needs</p> </td&gt