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HUD

AI agent evaluation platform and benchmarks

GTM Engineer

Sales OperationsConfirmed live in the last 24 hours
Full-time

About the Job

Requirements

  • At least 2 years of professional software engineering experience.
  • Strong proficiency in Python or TypeScript and fluency in SQL.
  • Experience building internal tools, automations, or integrations used by other teams on a daily basis.
  • Experience building data pipelines and API integrations between business systems.
  • Commercial judgment, including an interest in revenue outcomes, working with salespeople and customers, and prioritizing work that moves the pipeline.
  • Clear written communication and the ability to work with high agency in ambiguous, fast-moving environments.

Responsibilities

  • Own HUD’s go-to-market tooling end to end by choosing, setting up, integrating, and maintaining the tools used by the commercial team, and ensuring consistent use.
  • Build sourcing systems, including scrapers and enrichment pipelines, to find specific types of data supply at scale.
  • Own the data layer behind go-to-market by connecting CRM, marketplace, and product data into a clean, reliable source of truth for pipeline, listings, and revenue.
  • Build internal tools for the commercial team, including provider research and listing-quality checks, pipeline views, and forecasting views reviewed weekly by the founders.
  • Automate repetitive work across sourcing, qualification, routing, and reporting, and maintain system reliability as the team grows.
  • Introduce AI agents over time where they demonstrably outperform simpler automation.
  • Work with founders and the commercial team to identify the most manual, high-leverage bottlenecks and automate them first.
  • Make build-versus-buy decisions for go-to-market tooling and keep the tool stack simple.

Desired Qualifications

  • Experience in a RevOps engineering, growth engineering, sales engineering, or forward-deployed role.
  • Hands-on experience using large language models or AI agents in production, including evaluating their performance.
  • Early-stage startup experience or having founded an organization.
  • Familiarity with AI training data, including reinforcement learning environments, evaluations, and benchmarks.

About the Company

HUD

AI agent evaluation platform and benchmarks

HUD provides an evaluation platform for AI agents that perform computer-use tasks. It offers an interface that connects to HUD evaluation environments, allowing users to run benchmarks across hundreds of environments and thousands of tasks. Users can integrate their agents using various adapters, and interact with the system through an asynchronous API for efficient experiments. The platform then collects telemetry and benchmarking results to inform agent improvements. HUD differentiates itself by concentrating on evaluating and improving knowledge-work agents across a wide range of tasks and environments, rather than just building models, and by enabling scalable, tool-enabled testing via adapters and an asynchronous workflow. The company’s goal is to help organizations and developers assess, compare, and enhance their AI agents so they perform better in real-world knowledge-work scenarios.

Company size
11-50
Company stage
Seed
Total funding
$130K
Headquarters
San Francisco, CA
Founded
2025

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