Foundry (YC F24) Hiring Early Engineer to Build Web Agent Infrastructure

Summary

Location: San Francisco, CA Why Foundry Exists: Most of what people do at work sucks—it's manual, repetitive, and wastes time. Recruiters spend hours every day on LinkedIn, CRMs, email, and tedious data entry tasks instead of focusing on the things humans actually do well: building relationships, strategy, and decision-making. We're building tools so that AI agents can use web browsers exactly like humans, navigating enterprise apps like Salesforce, SAP, or Workday without constant manual intervention. Enterprises like Accenture staff entire teams and charge premium rates just to manage complex platforms like Salesforce, because navigating and operating these systems is so challenging. Right now, browser agents—even those built on GPT-o3—fail most of the time, get stuck on basic UI changes, and require endless manual debugging. This isn't sustainable. Foundry creates the infrastructure to fix this: precise simulations, robust evaluation tools, and direct support for AI labs trying to get these browser agents to actually work in the real world. We're applying the same proven playbook used by Waymo for autonomous vehicles and Scale AI for large language models—developing rigorous, reliable infrastructure to rapidly improve agent performance. Big players like OpenAI (Operator), Anthropic, and Mariner are investing heavily here, and it's clear why: McKinsey estimates around 60% of jobs have tasks that are automatable, representing over $15.8 trillion globally. We're at the front of this wave, creating essential tools that make AI-powered automation realistic and reliable. Who We’re Looking For: You're an elite engineer. You're impatient with bureaucracy and thrive when shipping real, foundational technology quickly. What You’ll Actually Do: Build and refine infrastructure for next-gen AI digital workers. Collaborate directly with top ML researchers and product leaders. Solve tough engineering challenges around browser automation, distributed systems, and ML in productio...