Full-Time
Software Engineer
Stagehand
Browserbase
51-200 employees
Cloud platform for hosting headless browsers
No salary listed
San Francisco, CA, USA
In Person
Relocation to San Francisco HQ possible.
 Software Engineering (1) |
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- Strong coding skills: preferably TypeScript; also valuable: Python/Go.
- Experience building developer tools, frameworks, or libraries that others depend on.
- Experience building AI agents/LLMs, distributed systems, or applying reinforcement learning.
- Familiarity with web automation frameworks (Puppeteer, Playwright, Selenium) or web scraping; Chrome DevTools Protocol experience is a huge bonus.
- Track record of open source contributions or public developer projects.
- Location and relocation: Willing to relocate to San Francisco, or currently in San Francisco.
- Build, operate, and grow the Stagehand framework — developer-first APIs with ~2 million monthly downloads and ~17k stars. Design and implement tools that make automating the web simple and powerful.
- Work with frontier AI labs (OpenAI, Google, and others) to improve models, benchmark capabilities, and make them more accessible to developers.
- Deploy production-ready AI solutions that impact millions of customers, shaping the future of the web.
- Help define, scope, and prioritize projects that shape the future of developer tooling.
- Document as you go and share your knowledge with the team.
- Chrome DevTools Protocol experience.
- Open source contributions or public developer projects.
- Experience building AI agents/LLMs, distributed systems, or applying reinforcement learning.
- Familiarity with web automation frameworks or web scraping is a plus (Puppeteer, Playwright, Selenium).
- Experience with distributed systems and reinforcement learning is desirable.
Browserbase provides a cloud platform for hosting, managing, and monitoring headless web browsers for developers and businesses that need automated web interactions such as web scraping, automated testing, and data extraction. It supports Puppeteer, Playwright, and Selenium, giving versatility across different automation tools. Users run their automation tasks in a fully managed, autoscaling environment that includes integrated proxies and anti-bot measures, so there is no need to manage underlying infrastructure. Debugging features like session recording and logging help identify and resolve issues quickly. The company differentiates itself by eliminating infrastructure setup and maintenance, focusing on offering a hassle-free, scalable environment. The goal is to make automated web tasks reliable and easy to run at scale without worrying about the underlying systems.
Company Size
51-200
Company Stage
Series B
Total Funding
$67.5M
Headquarters
San Francisco, California
Founded
2024
Simplify's Take
What believers are saying
- Microsoft's Fara-7B training on Browserbase boosts demand for scalable browser infrastructure.
- Vercel Marketplace launch enables production agents without CAPTCHA blocks via Web Bot Auth.
- $40M Series B from Notable Capital funds Director.ai no-code automation expansion.
What critics are saying
- ZenRows Puppeteer Cloud undercuts subscriptions with cheaper headless hosting in 6 months.
- Stagehand's 2M downloads drive AWS Lambda integrations, killing Functions in 3 months.
- Prime Intellect's BrowserEnv diverts AI labs with open Qwen fine-tuning in 12 months.
What makes Browserbase unique
- Browserbase partners with Microsoft and DeepMind for Fara-7B and Gemini evaluations on WebVoyager.
- Browserbase launches BrowserEnv with Prime Intellect for RL training on real websites.
- Browserbase integrates Exa-powered Search and $1/1k Fetch APIs for agent workflows.
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Benefits
Health Insurance
Flexible Work Hours
Company Equity
Growth & Insights and Company News
6 month growth
↓ -3%1 year growth
↑ 0%2 year growth
↓ -10%Introducing browserenv: train browser agents on real websites. Harsehaj Dhami Growth Engineer Kyle Jeong Growth Engineer March 25, 2026 TL;DR: Browserbase and Prime Intellect have partnered to launch BrowserEnv, a reinforcement learning environment for training and evaluating browser agents on real web tasks. Everyone wants AI models that can actually use the browser to get work done, but most models weren't trained to interact with real websites. They were trained on static datasets instead of environments where they can practice navigating pages, clicking elements, and completing multi-step workflows. This is why many browser agents look impressive in demos but struggle in real-world use. The missing piece is a reliable and scalable training environment. Training browser agents requires significant infrastructure when running browsers at scale, interacting with live websites without getting blocked, resetting sessions between tasks, and verifying results. This is the infrastructure frontier labs are already building. For example, Microsoft trained and evaluated their computer-use model Fara-7B using Browserbase, which required reliable access to real websites and scalable browser environments for evaluation and reinforcement learning workflows. Browserbase, Inc. has partnered with Prime Intellect to make this infrastructure accessible to everyone with BrowserEnv. BrowserEnv is a reinforcement learning environment designed specifically for training browser agents. It runs on Browserbase, which provides scalable browser infrastructure and access to real websites. Prime Intellect provides the training platform. Together, they make it possible to train and evaluate computer-use models on real browser tasks without building the infrastructure yourself. All you need is a dataset of tasks. Researchers and developers can train open models like Qwen or other computer-use models using reinforcement learning, while BrowserEnv handles browser orchestration, task execution, and verification. Training Qwen 3 VL on WebVoyager with BrowserEnv. To validate its stack end to end, Browserbase, Inc. fine-tuned Qwen/Qwen3-VL-8B-Instruct on real WebVoyager tasks using BrowserEnv and Prime Intellect. Browserbase, Inc. plugged the prime/webvoyager-no-anti-bot environment into Prime's RL pipeline, so the model could practice real navigation flows across sites like Amazon, Allrecipes, GitHub, Booking, and more without getting stuck on anti bot walls. BrowserEnv handled browser orchestration on Browserbase, Prime handled rollouts and optimization, and WebVoyager provided a standardized benchmark of 600 filtered tasks. Browserbase, Inc. started from the public WebVoyager environment in the Prime hub, switched it to CUA mode, and pointed it at Qwen3-VL-8B-Instruct. The training run used a relatively small but realistic configuration: 200 steps, batch size 32, 8 rollouts per example, learning rate 1e-4, and an oversampling factor of 2, with modest parallelism. model = "Qwen/Qwen3-VL-8B-Instruct" max_steps = 200 batch_size = 32 rollouts_per_example = 8 learning_rate = 0.0001 oversampling_factor = 2 max_async_level = 2 [sampling] max_tokens = 512 [[env]] id = "prime/webvoyager-no-anti-bot" args = {mode = "cua", viewport_width = 800, viewport_height = 600, keep_recent_screenshots = 2} In this setup, each training step created or reused a Browserbase session, loaded a WebVoyager task, and let Qwen3-VL act through coordinate based CUA primitives while a verifier judged task completion and produced reward signals. Over the course of the run, the model improved on multi step tasks such as searching, filtering, and extracting information from live pages, rather than just static HTML. The output of this training run is a LoRA adapter that can be easily deployed to run on the Prime Intellect platform. This training workflow is reproducible by anyone with access to a Browserbase and Prime Intellect account. You can even start from the same ingredients Browserbase, Inc. used: BrowserEnv on Browserbase, the WebVoyager no anti bot environment in Prime, and an open vision language model like Qwen3-VL. Frontier labs are already training browser agents this way, and now anyone with access to the internet can do the same. BrowserEnv is generally available today, learn more at browserenv.com and start training your own browser agents. Train your own custom modelLearn more
Introducing Browserbase Search. Thomas Katwan Software Engineer Harsehaj Dhami Growth Engineer March 17, 2026 TL;DR: Browserbase, Inc. is launching Browserbase Search, a simple API that lets agents search the web and get back relevant URLs to start navigating. It's powered by Exa and natively integrated into the Browserbase platform. Your agents need to search the web, just like humans. That sounds simple, but it turns out to be one of the first problems every agent runs into. When an agent doesn't know the exact URL it needs, it has to figure out where to start. That usually means running a search. Browserbase, Inc. has seen this pattern over and over again across Browserbase workloads. In fact, during its last billing cycle, Browserbase, Inc. saw 4.5 million requests to google.com run through its proxies. Search is one of the most common first steps agents take before navigating to the page where real work happens. Since Browserbase, Inc. already provide the agent infrastructure to interact with the web, Browserbase, Inc. thought it made sense to bring search into the platform as well. So Browserbase, Inc. built Browserbase Search, a Search API optimized for agents, accessible via its REST API, TypeScript and Python SDK with AI-native formats such as JSON, Markdown or HTML. Powered by Exa. To power the search layer, Browserbase, Inc. has partnered with Exa, which has built one of the best search APIs designed specifically for AI agents Exa's models are optimized for navigational queries, which typically run when agents are looking for a specific page or resource on the web. That makes it a natural fit for the types of workflows its customers and developers are already building on Browserbase. By combining Exa's search with its browser infrastructure, agents can now search for where they need to start and immediately navigate to it in just a few lines of code. The API. The Search API is intentionally simple. You send a query and get back the relevant results. import {Browserbase} from "@browserbasehq/sdk"; const bb = new Browserbase({ apiKey: process.env.BROWSERBASE_API_KEY!}); const searchResponse = await bb.search.web({ query: "a web browser for ai agents", numResults: 10,}); { "requestId": "string", "query": "a web browser for ai agents", "results": [{ "id": "string", "url": "string", "title": "string", "image": "Image URL if available", "favicon": "Image URL if available",}]} That's it. Every result returns a page url and when available, a title and description. Results are ranked by relevance, and optimized for navigational queries. An agent might search for relevant pages, fetch their contents, and then decide whether it needs to launch a browser to interact with a page. Search | (Fetch) | browse. Search helps the agent discover where to go, Fetch retrieves the page content, and browsers handle deeper interaction. Together, these primitives make it easier to build agents that can understand and navigate the web all in one platform. Get started. Search is available on all plans with 1,000 free searches per month, included. Read more in the docs. Happy searching!
Introducing Fetch: the simplest way to read the web. Harsehaj Dhami Growth Engineer March 11, 2026 TL;DR: Browserbase, Inc. launched a Fetch API for Browserbase. Give Browserbase, Inc. a URL and Browserbase, Inc. return the page content with no browser session required. It's fast, cheap, (~$1 / 1k pages), and perfect for agents that just need to read the web. Browserbase was built to help AI agents automate the web. It lets developers run browsers in the cloud to click buttons, fill forms, navigate applications, and automate complex workflows. But over time Browserbase, Inc. noticed something interesting: many developers were spinning up full browser sessions just to read the contents of a page. They weren't interacting with the site and they didn't need to click anything or run automation. They just wanted to see what was on the page. Sure, launching a browser for this works, but it's not the right primitive. Spinning up a full browser session to retrieve a page is a bit like killing a mosquito with a rocket launcher. It solves the problem, but it introduces unnecessary latency, cost, and complexity. So Browserbase, Inc. built the primitive that was missing: Fetch. Reading the web is often the first step. Agents frequently need to gather information from the web before they take action. They read documentation, inspect GitHub repositories, analyze product pages, and gather context before deciding what to do next. If you've used tools like Claude Code, you've already seen this pattern. Before executing complex actions, the model often fetches the contents of a page to understand what's there. It's the fastest way to make sense of the internet. Until now, doing this with Browserbase required launching a browser session. That meant additional infrastructure overhead even in cases where the task was simply retrieving the page content. The Fetch API solves this by letting you retrieve web content (both html and image) directly from Browserbase infrastructure without creating a browser session. Fetch a page with one request. The Browserbase Fetch API is intentionally simple. You provide a URL, and the API returns the page content. import Browserbase from "@browserbasehq/sdk"; const bb = new Browserbase({ apiKey: process.env.BROWSERBASE_API_KEY!}); const response = await bb.fetchAPI.create({ url: "https://httpbin.org/get",}); console.log(response.statusCode); console.log(response.content); The response: { "status_code":200, "headers":{ "Age":"6449", "Allow":"GET, HEAD", "Content-Encoding":"gzip", "Content-Type":"text/html", "Server":"cloudflare", "Vary":"Accept-Encoding"}, "content":"<!doctype html>...", "content_type":"text/html", "encoding":"utf-8", "id":"f47ac10b-58cc-4372-a567-0e02b2c3d479"} That's the entire API.:) Fetching pages reliably is harder than it sounds. At first glance, fetching a page might seem trivial. After all, tools like curl have existed for decades. But modern websites introduce complications that make reliable page retrieval more difficult than it appears. Redirects, inconsistent encodings, unusual headers, all make it harder to consistently retrieve the real content of a page. Its goal with the Browserbase Fetch API is simply, always return the page content. The API supports a few optional parameters such as output formatting and timeouts, but the main priority is making sure developers can depend on it to retrieve the page they requested. Browserbase, Inc. has prioritized reliability over a catalogue of shiny features. Fetch before you browse. Fetch becomes particularly powerful when used alongside browser automation. An agent first searches for relevant pages. It then fetches their contents to determine whether the page is useful. Only when deeper interaction is necessary does it launch a browser. This approach significantly reduces both latency and cost. Most pages don't really require full browser automation. They simply need to be read. Making Browserbase workflows cheaper. Running browsers is expensive infrastructure. Fetching pages is much lighter. Because of that, Browserbase, Inc. has just made Browserbase 10x cheaper, pricing the Fetch API at $1 per 1,000 pages. This allows agents to inspect far more of the web before deciding where to spend browser resources. In practice, this makes many Browserbase workflows dramatically cheaper while also improving performance. Win-win! The web is still the biggest API. The open web contains more data, workflows, and knowledge than any single API ever will. Documentation, research, software, and marketplaces all live there. Agents should be able to use that information easily. Fetching a page is often the first step in doing so, and now the Browserbase Fetch API makes that step simple. The Browserbase Fetch API is available today. Give it a URL, and Browserbase, Inc.'ll return the page. Get started with the docs here.
Browserbase is launching on the Vercel Marketplace. Paul Klein Founder & CEO Harsehaj Dhami Growth Engineer February 12, 2026 The best agents run on Vercel. Now they get the best browsers too. Today, Browserbase, Inc. is launching Browserbase on the Vercel Marketplace. With a single API key, Vercel customers can give their AI agents access to real, production-grade browsers without even running browsers themselves. Modern agents can now do a lot more than just calling APIs. They browse the web, logging into dashboards, scraping dynamic pages, filling out forms, and interacting with sites built for humans. And while it's easy to spin up a headless browser locally, doing it reliably in production is a very different problem. The problems scream at you when the headless setups break, bot detection gets in the way, and when observability is limited. Not to mention serverless platforms aren't optimized for running long-lived, stateful browser processes. That's where Browserbase steps in. Browserbase on the Vercel Marketplace. With Browserbase now available on the Vercel Marketplace, agents running on Vercel Sandbox can connect directly to remote browsers over CDP instead of launching a local browser inside their runtime. Your agent logic stays on Vercel's agent infrastructure, while the browser itself runs on infrastructure built for browser automation. In practice, this separation is what makes web agents viable in production. Browserbase, Inc. get real browsers that behave like real users, independent browser scaling that doesn't face serverless constraints, and complete session-level visibility into what your agents are doing on the web. Everything is wired together through Vercel Sandbox and the AI Gateway, and provisioned with a single API key. Browsing the web without getting blocked. Of course, running browsers is only half the battle. The other half is staying online. That's why Browserbase, Inc. is also announcing a Web Bot Auth partnership with Vercel. Browserbase now runs as a trusted agent, allowing participating websites to recognize legitimate, AI-driven browsing. Instead of constantly tripping bot detection or solving CAPTCHAs, agents can browse the web in a way that's observable and allowed. The result is more resilient automation and fewer workarounds, so agents can focus on actually doing useful work on real websites. A dedicated browser layer for agents on Vercel. Together, this partnership extends Vercel's agent cloud with a dedicated browser layer. Agents run where they should, and browsers run where they're observable and reliable. Authentication, provisioning, and billing live right in the Vercel Marketplace, and everything works together out of the box. Browserbase is available today for Vercel customers building agents that need to interact with the real web. If your agents need to browse, click, log in, or automate real sites, this is the missing piece that makes them production-ready by default.
Introducing Browserbase Functions. Adam McQuilkin Project Lead, Core Engineer Harsehaj Dhami Growth Engineer February 9, 2026 Browserbase makes it easy to run real browsers in production. But until now, using Browserbase still meant running your automation code somewhere else. That usually meant maintaining a second system just to keep Stagehand or Playwright scripts alive. Browserbase, Inc. has launched Browserbase Functions to remove this layer completely. Functions let you deploy agents and automations directly to Browserbase and run it next to the browser session it controls. You define, deploy, and invoke a function, and Browserbase handles execution, browser lifecycle, and results as one system. For teams, that means fewer moving parts and less infrastructure to operate. For automations, it means lower latency and fewer failure points. Functions are built for browser workloads, not generic request handlers. They support real Stagehand or Playwright code, long-running executions, and asynchronous invocation. Each function runs with a dedicated Browserbase session and returns structured results when it completes. Deployments are versioned by default. New code doesn't affect production until you explicitly promote it, so you can test changes safely without rewriting endpoints or workflows. Local development works the same way. When you run Functions locally, your code connects to real Browserbase browser sessions using your credentials. There's no mock environment to drift from production behaviour. Functions are available today for TypeScript! If you're already using Browserbase, you can move existing automations into Functions and stop managing separate runner infrastructure. If you're new, Functions give you a single place to run both the browser and the code that drives it. You can get started by initializing a Functions project: npx @browserbasehq/sdk-functions init If you want a deeper look at how Functions works and the engineering decisions behind it, Browserbase, Inc. has published a full technical deep dive as well. Browserbase Functions are the next step toward making browser automation faster and easier to run in production.