Head of Frontier AI at Invisible Technologies

New York - Hybrid; San Francisco Bay Area - HybridFull-timeCommercialPosted 2 days ago

About the Role

<div class="content-intro"><h2>About Invisible</h2> 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. 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. 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. 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.</div><h2>About the RL Data Lab</h2> 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. <h2>The role</h2> 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. Your mandate has three parts: <ul> <li>Grow existing clients by expanding scope, deepening multi-threaded relationships, and moving accounts from one-off projects to recurring programs.</li> <li>Win new clients across foundation labs, emerging frontier labs, large tech companies building genAI products, and enterprises training or fine-tuning models for agentic solutions.</li> <li>Build new revenue lines by bringing newer offerings (staff aug, data brokerage, agentic trajectories) to market alongside our core RLHF and SFT work.</li> </ul> <h3>Who you'll sell to</h3> <table> <thead> <tr> <th> Segment </th> <th> Who they are </th> <th> What they need from us </th> </tr> </thead> <tbody> <tr> <td> Foundation and frontier labs </td> <td> Labs training frontier models </td> <td> Post-training data, RL environments, agentic trajectories, specialist talent at scale </td> </tr> <tr> <td> Large tech companies </td> <td> Teams building genAI products and in-house models </td> <td> Domain-specific SFT/RLHF data, evals, embedded experts </td> </tr> <tr> <td> Enterprises </td> <td> Companies moving from buying AI to building or fine-tuning models for agentic workflows </td> <td> Proprietary-data fine-tuning, evaluation, trajectories for their own agents, staff aug </td> </tr> </tbody> </table> 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. <h3>What you'll sell</h3> You will sell a portfolio that spans our established services and the newer, more productized lines we are building. <table> <thead> <tr> <th> Offering </th> <th> What labs buy </th> <th> Where it is today </th> </tr> </thead> <tbody> <tr> <td> RL environments and long-horizon agentic trajectories </td> <td> Environments, tasks, graders, and multi-step agent trajectories for reinforcement learning </td> <td> Growth line; shaped closely with Product and Engineering </td> </tr> <tr> <td> RLHF / SFT </td> <td> Expert-generated preference data, demonstrations, and evaluations for post-training </td> <td> Core revenue; scale and margin expansion </td> </tr> <tr> <td> Staff augmentation </td> <td> Vetted domain experts and specialists embedded with lab teams on W-2 or 1099 terms </td> <td> New business unit; first deals and repeatable motion </td> </tr> <tr> <td> Data brokerage </td> <td> Licensed and sourced datasets matched to lab training needs </td> <td> New revenue line; packaging, pricing, and first buyers </td> </tr> </tbody> </table>   <h2>Responsibilities</h2> Revenue and growth <ul> <li>Own the model-builder revenue number across labs, tech companies, and enterprises: bookings, net revenue retention, and new-logo targets.</li> <li>Build and run the account plan for each key account, including whitespace mapping across all four offerings.</li> <li>Source, scope, price, and close new programs; lead negotiations on MSAs, SOWs, and commercial terms.</li> <li>Forecast accurately and run a disciplined pipeline that leadership can plan against.</li> </ul> Client relationships <ul> <li>Be the senior relationship owner with research leads, post-training and AI platform teams, data leads, and procurement at each account.</li> <li>Multi-thread every account so relationships do not depend on a single champion.</li> <li>Run executive business reviews and turn delivery results into expansion.</li> <li>Escalate and resolve delivery issues before they put renewals at risk.</li> </ul> Product and business transformation <ul> <li>Bring structured customer insight to Product and Engineering: what each segment is training on next, where data bottlenecks are, and what they will pay for.</li> <li>Co-define packaging and pricing for productized offerings, moving revenue from bespoke services toward repeatable, higher-margin products.</li> <li>Pilot new revenue lines (staff aug, data brokerage, agentic trajectories) with early-adopter clients and turn pilots into standard offerings.</li> <li>Partner with Delivery and Operations to make sure what is sold can be delivered at quality and margin.</li> </ul> Team and market <ul> <li>Build and lead a team of account executives and engagement leads as the business scales.</li> <li>Represent Invisible in the frontier AI community through conferences, research relationships, and thought leadership.</li> <li>Track competitors and market pricing, and feed that into positioning and strategy.</li> </ul> <h2>What success looks like</h2> First 90 days <ul> <li>Meet the senior stakeholders at every active key account and have a written account plan for each.</li> <li>Own the model-builder pipeline and forecast across all three segments, with a clear view of expansion and new-logo targets.</li> <li>Close or advance at least one deal in a new revenue line (staff aug, data brokerage, or agentic trajectories).</li> <li>Agree with Product and Engineering on the top customer-driven priorities for the next two quarters.</li> </ul> First year <ul> <li>Hit the model-builder revenue target, with growth from both existing and new accounts.</li> <li>Measurably shift revenue mix toward productized, recurring offerings.</li> <li>Land new logos in each segment, including first enterprise model-building programs, and multi-thread every top account.</li> <li>Have a hired, ramped team running a repeatable sales motion.</li> </ul> <h2>Qualifications</h2> Required <ul> <li>10+ years in enterprise sales, business development, or account leadership, including 3+ years leading a team or a major book of business.</li> <li>Existing, senior relationships at one or more foundation or frontier AI labs, plus credibility with AI leaders at large tech companies or enterprises.</li> <li>A track record of closing and expanding multi-million-dollar, multi-year deals with technical buyers.</li> <li>Working fluency in how frontier models are built: pretraining, SFT, RLHF, RL environments, evals, and agentic systems.</li> <li>Experience selling a portfolio that blends services and technology, with strong commercial instincts on pricing, packaging, and margin.</li> <li>Proven ability to work cross-functionally with Product, Engineering, and Delivery to shape what gets built.</li> </ul> Preferred <ul> <li>Prior leadership at an AI data, training, or evaluation company, or on the data side of a frontier lab.</li> <li>Experience taking a services business toward productized or platform revenue.</li> <li>Exposure to staffing, talent marketplaces, or data licensing models.</li> <li>Experience selling AI/ML platforms or services into enterprises adopting agentic AI.</li> <li>Technical background (CS, ML, or a quantitative field).</li> </ul> <h2>Who you are</h2> <ul> <li>Credible with researchers and enterprise buyers alike. You can hold a credible conversation about reward models, eval design, and agent trajectories, not just commercial terms.</li> <li>A builder, not just a closer. You see a recurring customer need and push to turn it into a product.</li> <li>Comfortable with ambiguity. New offerings will be half-formed when you start selling them; you help shape them.</li> <li>Operationally rigorous. Clean pipeline, honest forecasts, clear account plans.</li> <li>Low ego, high ownership. You lead from the front on deals and give credit to the teams who deliver.</li> </ul> <h2>What’s In It For You</h2> Invisible is committed to fair and competitive pay, ensuring that compensation reflects both market conditions and the value each team member brings. Our salary structure accounts for regional differences in cost of living while maintaining internal equity.<div class="content-conclusion">You can find more information about our geographic pay tiers <a class="c-link" href="https://invisibletech.ai/compensation-and-pay-tiers" target="_blank" data-stringify-link="https://invisibletech.ai/compensation-and-pay-tiers" data-sk="tooltip_parent">here</a>. During the interview process, your Invisible Talent Acquisition Partner will confirm which tier applies to your location. For candidates outside the U.S., compensation is adjusted to reflect local market conditions and cost of living. *Bonuses and equity are included in all full-time offers. Final compensation is determined by a combination of factors, including location, job-related experience, skills, knowledge, internal pay equity, and overall market conditions. Because of this, every offer is unique. Additional details on total compensation and benefits will be discussed during the hiring process. <h2>What It's Like to Work at Invisible:</h2> At Invisible, we’re not just redefining work—we’re reinventing it. We operate at the intersection of advanced AI and human ingenuity, pushing the boundaries of what’s possible to unlock productivity and scale. Ownership is at the core of everything we do. Here, you won’t just execute tasks—you’ll build, innovate, and shape the future alongside world-class clients pushing the boundaries of AI. We expect bold ideas, relentless drive, and the ability to turn ambiguity into opportunity. The pace is fast, the challenges are big, and the growth is unmatched. We’re not for everyone, and we’re okay with that. If you’re looking for predictable routines, this isn’t the place for you. But if you’re driven to create, thrive in dynamic environments, and want a front-row seat to the AI revolution, you’ll fit right in. Country Hiring Guidelines: Invisible is a hybrid organization with offices and team members located around the world. While some roles may offer remote flexibility, most positions involve in-office collaboration and are tied to specific locations. Any location-based requirements or hybrid expectations will be communicated by our Talent Acquisition team during the recruiting process. AI Interviewing Guidelines: Our hiring team thoughtfully uses AI to support an efficient, engaging, and inclusive interview process. Since AI can also be a helpful tool for candidates, we've outlined expectations for using it ethically throughout your interview journey. <a class="c-link" style="color: rgb(35, 111, 161);" href="https://www.invisible.co/ai-interview-guidelines" target="_blank" data-stringify-link="https://www.invisible.co/ai-interview-guidelines" data-sk="tooltip_parent">Click here to learn more about how we use AI and our guidelines for candidates.</a> Accessibility Statement: We are committed to providing reasonable accommodations for individuals with disabilities. If you require an accommodation to participate in the application or interview process, please submit your request using our accommodation request form. A member of our team will follow up to support your request. Here is the link the google form: <a class="_ymio1r31 _ypr0glyw _zcxs1o36 _mizu1v1w _1ah3dkaa _ra3xnqa1 _128mdkaa _1cvmnqa1 _4davt94y _4bfu1r31 _1hms8stv _ajmmnqa1 _vchhusvi _kqswh2mm _ect4ttxp _syaz13af _1a3b1r31 _4fpr8stv _5goinqa1 _f8pj13af _9oik1r31 _1bnxglyw _jf4cnqa1 _30l313af _1nrm1r31 _c2waglyw _1iohnqa1 _9h8h12zz _10531ra0 _1ien1ra0 _n0fx1ra0 _1vhv17z1" style="color: rgb(35, 111, 161);" href="https://docs.google.com/forms/d/e/1FAIpQLScqsu0PCQ0m0lwt-VFeXovNbZxWk0jogv8QI_ciGqZsIbSBjQ/viewform?usp=sharing&ouid=102356854798492362557" data-renderer-mark="true" data-is-router-link="false" data-testid="link-with-safety">https://docs.google.com/forms/d/e/1FAIpQLScqsu0PCQ0m0lwt-VFeXovNbZxWk0jogv8QI_ciGqZsIbSBjQ/viewform?usp=sharing&ouid=102356854798492362557</a> Equal Opportunity Statement: We’re an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, or veteran status, or any other basis protected by law. Due to a high volume of candidates, Invisible may use automated decision-maker technologies to filter candidates based on response to our application questions and other provided information. Our use of automated decision-making enables us to be efficient by providing a manageable list of possible candidates that meet our mandatory hiring criteria. If you object to our use of automated decision-making please contact us. </div>

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