About HUD

HUD's mission is to build reliable, fair and open infrastructure for AI data. We want data to be valuable for the people who create it and trustworthy for the labs that train on it. Our team is a quickly growing group of researchers, engineers and operators building the economy that shapes what AI will become. Backed by $16M from top VCs and YC (W25), our marketplace and platform are used by startups, Fortune 500 companies and frontier labs.

About the role

We’re looking for a software engineer who wants to work on the commercial side of the business.

HUD runs a two-sided marketplace. Frontier AI labs tell us what data they need, and our commercial team finds the businesses and individuals who have it and gets them listed. As that team scales, the constraint is no longer headcount but systems.

As our GTM Engineer, you’ll treat go-to-market as a software problem. You’ll own HUD’s GTM tooling and build the scaled systems, data pipelines and internal tools that the whole commercial team uses every day, so a small team can source, qualify and close at many times its size. Think of it as a RevOps engineer role: an engineer first, with the commercial judgement to know what’s worth building.

Responsibilities

Own HUD’s GTM tooling end to end: choose, set up, integrate and maintain the tools the commercial team relies on, and make sure everyone uses them the same way.

Build sourcing systems, such as scrapers and enrichment pipelines, that find specific kinds of data supply at scale.

Own the data layer behind GTM: connect our CRM, marketplace and product data into a clean, reliable source of truth for pipeline, listings and revenue.

Build internal tools that everyone on the commercial team uses, from provider research and listing-quality checks to the pipeline and forecasting views the founders review every week.

Automate repetitive work across sourcing, qualification, routing and reporting, and keep those systems reliable as the team grows. Over time, bring in AI agents where they clearly beat simpler automation.

Work with the founders and the commercial team to find the most manual, highest-leverage bottlenecks, and automate those first.

Make build-versus-buy calls on GTM tooling and keep the stack simple.

Experience

You may be a good fit if you have

2+ years of professional software engineering experience.

Strong Python or TypeScript, and fluent SQL.

Experience building internal tools, automations or integrations that other teams rely on every day.

Experience building data pipelines and API integrations between business systems.

Commercial judgement: you care about revenue outcomes, enjoy working with salespeople and customers, and prioritise what actually moves the pipeline.

Clear written communication and high agency in ambiguous, fast-moving environments.

Strong candidates may also have

Experience in a RevOps engineering, growth engineering, sales engineering or forward-deployed role.

Hands-on experience using LLMs or AI agents in production, including evaluating how well they work.

Early-stage startup experience, or founded something yourself.

Familiarity with AI training data, e.g., you know what RL environments, evals and benchmarks are.

We prioritize technical aptitude and learning potential over years of experience. Motivated candidates are encouraged to apply even if they don't meet all criteria.

Team & company details

You’ll work closely with the founders and HUD’s commercial team, including our hunters, BD leads and SDRs, and with our engineering team.

Team Size: ~25 people currently, mostly full-time in-person, but some remote.

Our team: Our team brings together five International Olympiad medalists across IOI, ILO and IPhO, researchers published at NeurIPS and ICLR, and engineers and researchers from Google DeepMind, Amazon, AWS, Meta, Qwen, GLM, and Mercor. It also includes operators from BCG and Uber, the first security hire at one of the largest crypto exchanges, serial AI startup founders, former quant researchers, artists and the former #1 ranked Catan player in the world.