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DepthFirst

Autonomous agents audit code for vulnerabilities

Product Engineer

Frontend EngineeringConfirmed live in the last 24 hours
Full-timeSan Francisco, CA, USAIn-person

About the Job

Requirements

  • At least 3 years of professional experience in front-end engineering, with a deep understanding of React, JavaScript/TypeScript, and Postgres (Neon).
  • Proven experience optimizing large-scale web applications for performance, scalability, and maintainability.
  • Expertise in developing reusable user interface frameworks, libraries, and tools.
  • Familiarity with state management libraries such as Redux or Zustand and modern CSS frameworks such as Tailwind CSS.
  • Strong understanding of web fundamentals, including HTTP, browser rendering pipelines, and web performance metrics.
  • Attention to detail, a product mindset, and a desire to build user-centric products.

Responsibilities

  • Develop and design AI-first products that solve real challenges.
  • Own front-end performance to ensure the website meets and exceeds industry benchmarks for speed and responsiveness.
  • Work extensively with Next.js, React, and modern web development practices to create robust, scalable, and performant solutions.
  • Develop and design the web application serving customers and remediate software vulnerabilities at scale.
  • Drive the product, understand users, and reimagine how companies do security.

Desired Qualifications

  • Knowledge of Next.js is a bonus.

About the Company

DepthFirst

Autonomous agents audit code for vulnerabilities

DepthFirst builds autonomous agents that understand a company’s code, business logic, and infrastructure end-to-end to surface security weaknesses and propose fixes that are ready to merge. The platform, called General Security Intelligence, uses AI agents to analyze an organization’s codebase and systems, identify vulnerabilities, and suggest actionable patches that can be integrated into the codebase. It stands out from traditional static analysis by delivering more true-positive findings (about 8x higher) and far fewer false positives (roughly 85% fewer), and it shows strong performance on CyberGym benchmarks. Early customers include AngelList, Supabase, Moveworks, Persona, and Lovable. The company aims to speed up secure software development by automatically finding problems and providing ready-to-implement fixes, and it is expanding research, go-to-market efforts, and hiring after a $40 million Series A round in January 2026.

Company size
51-200
Company stage
Series B
Total funding
$140.8M
Headquarters
San Francisco, CA
Founded
2024

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