Head of Frontier AI at Invisible Technologies in New York, NY

Job description

About Invisible Invisible is an Applied AI research company closing the gap between frontier models and the enterprise. We provide the platform infrastructure that makes AI work in production at scale: unify fragmented data, map complex processes, orchestrate and evaluate agents, and stand up hyper-personalized workflow applications fast for companies like Grubhub, Alliance Global, and Thomson Reuters. Where models fall short, we build RL environments and data to fix them. The result: a virtuous cycle between enterprise deployment and model training. Recognized as Best Predictive Analytics Platform of the Year at the 2026 AI Breakthrough Awards, Invisible makes AI work. About the RL Data Lab 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. The role 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: Grow existing clients by expanding scope, deepening multi-threaded relationships, and moving accounts from one-off projects to recurring programs. 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. Build new revenue lines by bringing newer offerings (staff aug, data brokerage, agentic trajectories) to market alongside our core RLHF and SFT work. Who you'll sell to Segment Who they are What they need from us Foundation and frontier labs Labs training frontier models Post-training data, RL environments, agentic trajectories, specialist talent at scale Large tech companies Teams building genAI products and in-house models Domain-specific SFT/RLHF data, evals, embedded experts Enterprises Companies moving from buying AI to building or fine-tuning models for agentic workflows Proprietary-data fine-tuning, evaluation, trajectories for their own agents, staff aug 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. What you'll sell You will sell a portfolio that spans our established services and the newer, more productized lines we are building. Offering What labs buy Where it is today RL environments and long-horizon agentic trajectories Environments, tasks, graders, and multi-step agent trajectories for reinforcement learning Growth line; shaped closely with Product and Engineering RLHF / SFT Expert-generated preference data, demonstrations, and evaluations for post-training Core revenue; scale and margin expansion Staff augmentation Vetted domain experts and specialists embedded with lab teams on W-2 or 1099 terms New business unit; first deals and repeatable motion Data brokerage Licensed and sourced datasets matched to lab training needs New revenue line; packaging, pricing, and first buyers Responsibilities Revenue and growth Own the model-builder revenue number across labs, tech companies, and enterprises: bookings, net revenue retention, and new-logo targets. Build and run the account plan for each key account, including whitespace mapping across all four offerings. Source, scope, price, and close new programs; lead negotiations on MSAs,