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Invisible Tech

Head of Frontier AI

New York - Hybrid; San Francisco Bay Area - Hybrid; New York; San FranciscoHybrid · United States
Director+ · Commercial
POSTED 16 OCT
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Pay · Invisible Tech
$144k–$172k
p25–p75 · n=3
Open for
21d
since 16 Oct
Hiring · 30d
23
0 net · open roles
LLMs

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, SOWs, and commercial terms.
  • Forecast accurately and run a disciplined pipeline that leadership can plan against.
Source · Invisible TechFirst seen 2 NovOriginal ↗