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HUD

Live runtime data for AI coding

Head of Talent

Generalist Recruiting +1Confirmed live in the last 24 hours
Full-timeSan Francisco, CA, USA

About the Job

Requirements

  • Experience hiring engineering, product, and go-to-market roles.
  • Comfort evaluating candidates through portfolios and projects, not only resumes.
  • Ability to understand and communicate technical concepts credibly with candidates.
  • Ability to manage multiple roles and recruiting pipelines simultaneously.
  • Strong judgment in assessing talent quality and setting hiring standards.
  • Early-stage startup experience and ability to work independently in fast-paced environments.

Responsibilities

  • Own end-to-end recruiting across technical and go-to-market roles.
  • Build and optimize recruiting operations and tooling, automating workflows whenever possible.
  • Partner with founders and team leads to define role requirements, evaluation criteria, and interview processes.
  • Develop a strong understanding of the product to effectively pitch technical candidates.
  • Source top candidates through high-signal and unconventional channels.
  • Screen candidates for technical competence and product/market intuition.
  • Support onboarding and new-hire ramp.
  • Help define and run performance-review processes, leveling, and feedback systems.

Desired Qualifications

  • A track record of creative sourcing.
  • Familiarity with Ashby, Juicebox, and Clay.
  • Experience with vibe coding and using artificial intelligence to automate workflows.
  • Exposure to or ownership of people or human-resources functions.
  • Experience evaluating non-traditional candidate profiles.

About the Company

HUD

Live runtime data for AI coding

HUD builds a Runtime Code Sensor that links live production software with AI-powered coding assistants. Developers add a lightweight SDK to their apps to stream real-time information about how code behaves—such as errors, latency, performance, and how functions are used—directly to AI tools like GitHub Copilot and other code generators. The product works by feeding ongoing, context-rich data from a running system into AI models so generated code can be aware of real-world conditions rather than just static code. This makes AI-generated code safer and more reliable in production. HUD differentiates itself by enabling production-aware development, providing continuous feedback from live environments rather than relying on static analysis or old logs. The company’s goal is to help software teams build higher-quality software faster with fewer bugs and better performance by bridging the gap between AI-generated code and real-world usage.

Company size
51-200
Company stage
Early VC
Total funding
$21.2M
Headquarters
San Francisco, CA
Founded
2025

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