E

E2B

Cloud-based sandboxed AI development platform

Founding Product Marketing Lead

Full-Time
$170k - $230k/yr+ Equity
Senior
San Francisco, CA, USA
HybridFour days on-site and one day working from home each week.
Growth & MarketingProduct Marketing

About the job

Requirements
  • Have at least 5 years of experience in product or developer marketing for a technical product, including a period as the sole marketer.
  • Provide a portfolio of technical pieces personally written for a developer audience and be able to read code well enough to write about sandboxing, isolation, and runtime security.
  • Have developed product positioning from scratch and launched products adopted by engineers.
  • Understand usage-based pricing for infrastructure or have relevant adjacent pricing experience.
  • Have served as the second person on a product marketing team and be ready to lead product marketing decisions.
  • Be comfortable being measured on signups and pipeline, not just traffic.
Responsibilities
  • Develop E2B's positioning and messaging, defining what it is, its audience, its differentiation, and how that evolves with the agent market.
  • Own product launches, including narrative, assets, sequencing, distribution, launch cadence, and coordination with engineering.
  • Create the content engine, including technical articles, comparison and migration pages, customer stories, launch content, and website content; write initial flagship pieces and run the technical writer and video producer who scale production.
  • Own the packaging story for usage-based infrastructure pricing and competitive positioning used by sales and self-service customers.
  • Build sales enablement materials, including decks, one-pagers, objection handling, and proof points.
  • Propose and own a budget for paid programs, sponsorships, tools, and freelancers.
  • Establish the product marketing function and grow it as the company grows.
  • In the first 90 days, write the positioning document with input from founders, sales, and key customers; publish two customer stories and two flagship technical pieces; run one launch end to end; and create a content and launch calendar for the following two quarters with a rationale.
  • Drive outcomes assessed by whether people outside the company can explain E2B, launch cadence and reach, content-attributed signups, enterprise pipeline citing published content, and the quality of work shipped by the writer and video producer.
Desired Qualifications
  • Experience with agent frameworks, model infrastructure, or sandboxes.
  • Familiarity with answer-engine optimization or search engine optimization programs.
  • A track record of tying content to pipeline at a high-growth startup.

About the company

E

E2B

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Website

E2B builds tools and cloud infrastructure for AI developers, with a primary ChatGPT plugin that connects to a full sandboxed cloud environment running on E2B’s own infrastructure. It works by integrating with ChatGPT’s code interpreter, giving developers a cloud workspace to write, test, and run AI-driven code in a secure, isolated environment where memory, security, and data privacy are managed by the platform. E2B differentiates itself with a tightly integrated, cloud-backed development setup centered on a secure sandbox and developer-focused tooling, rather than generic cloud services or AI APIs. The goal is to help developers build reliable, scalable AI applications faster by providing a secure, efficient, and easy-to-use development environment.

Company Size

51-200

Company Stage

Series A

Total Funding

$32.1M

Headquarters

San Francisco, California

Founded

2023

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Simplify Jobs

Simplify's Take

What believers are saying

  • June 2026 Stripe Projects support opens a direct channel to AI builders.
  • June 2026 StackAI reported hundreds of thousands of production sandboxes on E2B.
  • August 2026 company sources claimed one billion cumulative launches and seven million downloads.

What critics are saying

  • January 13, 2026 control-plane failure blocked new sandboxes, exposing platform fragility.
  • Cloudflare and Daytona compress pricing and distribution, pressuring E2B's sandbox moat.
  • If open-source adoption stalls, E2B's enterprise cloud becomes a feature, not a company.

What makes E2B unique

  • Firecracker microVM sandboxes and open-source runtime anchor E2B's security story.
  • Docker partnership shipped 200-plus MCP tools inside sandboxes on October 23, 2025.
  • OpenAI Agents SDK support and Stripe Projects integration embed E2B across agent workflows.

Help us improve and share your feedback! Did you find this helpful?

Benefits

  • Health Insurance
  • Vision Insurance
  • Dental Insurance
  • Unlimited Paid Time Off
  • Flexible Work Hours
  • Hybrid Work Options
  • Remote Work Options
  • Paid Vacation
  • Wellness Program
  • Mental Health Support
  • Gym Membership
  • Phone/Internet Stipend

Growth & Insights and Company News

Headcount

6 month growth

-2%

1 year growth

2%

2 year growth

0%
CreateOS
Aug 5th, 2026
Cloudflare Sandbox pricing, compared: what drives the bill.

Cloudflare Sandbox pricing, compared: what drives the bill. Cloudflare Sandbox pricing explained with a worked cost model, compared against E2B and Daytona - and why idle time and egress decide the bill. CreateOS · August 5, 2026 How much does a Cloudflare Sandbox cost? Cloudflare Sandboxes run on the Containers billing model: a $5/month Workers Paid plan, then CPU at $0.000020 per vCPU-second, memory at $0.0000025 per GiB-second, and disk at $0.00000007 per GB-second. The plan includes 375 vCPU-minutes, 25 GiB-hours of memory and 200 GB-hours of disk before overage. Those rates are published in the Cloudflare Workers pricing docs and were checked on 5 August 2026. Sandbox pricing changes; re-check before you budget on it. The per-unit rate is the easy part. What decides your bill is which units you are charged for while the agent is doing nothing. Why per-second rates do not tell you the cost. An AI agent spends most of its wall-clock life waiting - on a model response, a tool call, a human approval. A code-execution benchmark runs flat out. An agent does not. That gap matters because vendors bill idle time differently: * Cloudflare bills CPU on active usage only - a change made in its November 2025 CPU pricing update - but bills memory on provisioned resources for as long as the sandbox exists. * E2B bills vCPU and RAM per second of sandbox lifetime, whether or not the CPU is busy. * Daytona publishes a Windows rate of $0.0858/vCPU/h and $200 in free compute, but does not publish a general per-second rate on its pricing page. So a comparison table of rates can rank three vendors in an order that reverses the moment your agent starts waiting. What does a realistic agent workload actually cost? Take 1,000 agent sessions a month, five minutes each, on 2 vCPU and 4 GiB of RAM, with the CPU genuinely busy about 20% of the time. That is 83.3 hours of wall-clock sandbox time and 300,000 sandbox-seconds. Working it through on published rates: Cloudflare | Component | Quantity | Included | Billable | Cost | | CPU (active only, ~20%) | 120,000 vCPU-s | 22,500 | 97,500 | $1.95 | | Memory (provisioned, full session) | 1,200,000 GiB-s | 90,000 | 1,110,000 | $2.78 | | Workers Paid plan | - | - | - | $5.00 | | Total | / | / | / | ≈ $9.73 | E2B, billed on sandbox lifetime at $0.000028/s for 2 vCPU and $0.0000045/GiB/s: | Component | Quantity | Cost | | vCPU | 300,000 s | $8.40 | | RAM | 1,200,000 GiB-s | $5.40 | | Usage total | / | ≈ $13.80 | E2B's Hobby tier is free with a one-time $100 credit, so that usage is covered for a while. Its Pro tier adds $150/month on top. Both figures exclude egress and disk. That omission is the point of the next section. Which costs do sandbox pricing pages hide? Egress and idle memory are where an agent bill grows faster than the compute line. Neither appears in a per-second rate comparison. Three things to check before you commit: * Egress. Cloudflare charges $0.025-$0.05 per GB beyond an included 500 GB-1 TB, varying by region. An agent that pulls large documents or writes artifacts to external storage moves real volume. * Idle memory. If memory is billed on provisioned resources, a sandbox left alive between turns bills the whole time - which is exactly the pattern a conversational agent produces. * Monthly floors. A $150/month plan is irrelevant at scale and dominant at pilot scale. Model your actual volume, not the vendor's headline tier. Cloudflare's own Sandbox SDK docs are the primary source for what a sandbox does; the pricing page is the primary source for what it costs. Read both. How does CreateOS price sandboxes? CreateOS publishes a pricing model rather than a rate card: per-second billing of vCPU and memory, no egress fees, no minimums and no monthly commitment. The AI Gateway is a flat 2.5% platform fee on the lowest available rate across nine providers. CreateOS is not going to print a per-second number here that CreateOS would then have to keep in sync. CreateOS pricing models usage with you directly, because the honest answer for an agent workload depends on your idle ratio and your egress volume, and a headline rate hides both. What is worth comparing is the model, not the number: | / | Idle CPU billed | Egress charged | Monthly floor | | Cloudflare | No (active only) | Yes, beyond allowance | $5 | | E2B | Yes (lifetime) | Not published as separate | $0 Hobby / $150 Pro | | CreateOS | Per-second vCPU + memory | No egress fees | None published | If your agents are chatty and move data, the egress line is the one to model first. Should you pick a sandbox on price? Usually not - pick on isolation model and state handling, then check the price is not disqualifying. The cost difference between these providers on a pilot workload is single-digit dollars a month. The cost of choosing an isolation boundary your security team later rejects is a re-platform. Start with what an AI agent sandbox is if you are still scoping, and with Firecracker sandboxes if the question is what the boundary actually guarantees. Common questions. Cloudflare Sandboxes bill on the Containers model: a $5/month Workers Paid plan, then $0.000020 per vCPU-second of active CPU, $0.0000025 per GiB-second of memory, and $0.00000007 per GB-second of disk. The plan includes 375 vCPU-minutes, 25 GiB-hours and 200 GB-hours before overage. Figures checked 5 August 2026. Is Cloudflare Sandbox cheaper than E2B? On a modelled workload of 1,000 five-minute sessions at 2 vCPU and 4 GiB, Cloudflare came to roughly $9.73 and E2B to roughly $13.80 in usage, before egress. The gap narrows or reverses depending on your idle ratio, because Cloudflare bills CPU only when active while E2B bills for the sandbox lifetime. Does Cloudflare charge for sandbox egress? Yes. Network egress is $0.025-$0.05 per GB depending on region, with an included allowance of 500 GB to 1 TB per month. For agents that move documents or write artifacts externally, this line can exceed the compute line. What is Daytona sandbox pricing? Daytona's pricing page publishes $200 in free compute, the first 5 GiB of storage free, and a Windows rate of $0.0858 per vCPU-hour. It does not publish a general per-second Linux rate, so a like-for-like comparison needs figures from their sales team. Why is my AI agent sandbox bill higher than the rate card suggests? Almost always idle time and egress. Agents wait on model responses and tool calls, so wall-clock sandbox lifetime is several times actual CPU work - and if memory is billed on provisioned resources, you pay for all of it. Check whether your provider bills idle CPU, and model egress separately. CreateOS bills per second of vCPU and memory with no egress fees, no minimums and no monthly commitment, and charges a flat 2.5% platform fee on the AI Gateway's lowest available provider rate. Exact rates are modelled against your usage rather than published as a rate card. About CreateOS. CreateOS is the unified AI execution layer for the enterprise - route, govern, validate, observe. It runs agent workloads in Firecracker/KVM micro-VM sandboxes with fork, pause-resume, VPC and S3-backed disks, with kernel-level egress control via eBPF, and can run entirely inside a customer's own boundary. Built by the team at NodeOps. Next step. Model your own numbers before you choose. Take your session count, average session length, vCPU and memory, and an honest idle ratio, then run them through the arithmetic above against each provider's published rates.

Stack AI
Jun 18th, 2026
StackAI partners with E2B to give every agent a computer.

StackAI partners with E2B to give every agent a computer. Jun 18, 2026 StackAI and E2B have partnered to bring secure, isolated code execution to enterprise AI agents in regulated industries. The partnership now powers three core capabilities on the StackAI platform. Custom Code lets users execute Python or JavaScript inside agent workflows, with every run automatically sandboxed. Computer Use and RPA replays recorded desktop sessions inside E2B sandboxes so agents can operate enterprise software securely and reliably. Browser Use keeps web navigation and scraping sessions fully isolated. "With E2B, it's really easy to provision sandboxes. They're secure by default, highly capable, and very performant," says JJ Miller, Senior Product Manager. "Sandboxes are a key primitive for agents going forward. For us to keep growing as a company, we need a partner that can grow with us. We're happy to have found one in E2B." The collaboration scaled quickly, going from a few sandboxes during evaluation to hundreds of thousands in production. And it's set to deepen, according to JJ: "Sandboxes are a key primitive for agents going forward. For us to keep growing as a company, we need a partner that can grow with us - we're happy to have found one in E2B." Read the full story here. Pratik paudel. Engineering at StackAI Make your organization smarter with AI. Deploy custom AI Assistants, Chatbots, and Workflow Automations to make your company 10x more efficient.

ideavo.ai
Mar 22nd, 2026
Why Ideavo uses E2B sandboxes.

Why Ideavo uses E2B sandboxes. If AI can generate code, it also needs a place to run that code. That is exactly why Ideavo is writing this blog. A lot of builders see "sandbox" in Ideavo and understand that it is part of the product, but not necessarily why it exists, why Ideavo ask for an E2B key, or why Ideavo chose this setup in the first place. The short answer is simple: generated code needs a real execution environment, and Ideavo believe that environment should stay transparent, affordable, and under your control. That is why Ideavo integrates with E2B instead of hiding code execution behind its own servers. What is a sandbox? A sandbox is an isolated runtime environment where code can run safely without affecting the rest of your system. Think of it as a separate computer created just for the task at hand. Code can run there, dependencies can be installed, files can be created, and commands can be executed, all inside an isolated environment instead of directly on your machine or inside shared platform infrastructure. That isolation matters a lot when AI is involved, because generated code is only useful if it can actually be executed, tested, and refined in a real environment. Why is a sandbox required? AI-generated code is not finished the moment it is written. It usually needs to be: * executed * tested * debugged * iterated on * connected to files, packages, or terminal commands Without a sandbox, an AI product can generate code, but it cannot meaningfully run that code in a secure and controlled way. That makes the sandbox essential. It is the execution layer that turns generated code into a working development loop. If you want an app builder to do more than just output code snippets, it needs a real runtime behind it. What is E2B? E2B is an open-source runtime for executing AI-generated code in secure cloud sandboxes. E2B describes its sandbox as a fast, secure Linux VM created on demand for an agent, with support for running code, commands, filesystems, and more. In simple terms, E2B gives AI products a dedicated isolated computer in the cloud where generated code can actually run. That makes it a strong fit for products like Ideavo, where code execution is part of the product experience, not just an optional extra. Why Ideavo asks you to bring your own E2B account. Because Ideavo want sandbox execution to stay transparent, affordable, and under your control. 1. Cost: Ideavo gives cost-to-cost API usage. Ideavo is built around transparent usage. The same principle applies to sandbox execution. Running its own managed sandbox layer for every user would mean adding another infrastructure cost on top of the platform. That would either introduce markup or force sandbox usage into a more opaque bundled pricing model. Ideavo do not want that. By asking you to connect your own E2B account, sandbox billing stays direct. You pay E2B for sandbox compute, and that compute remains outside a hidden platform markup layer. That keeps the model simple:Ideavo handles the product experience.E2B handles the sandbox runtime.You keep visibility into where compute costs come from. E2B also publicly states that new users receive $100 in free credits, which is enough to get started and can cover multiple projects depending on usage. 2. Ownership and security: your code runs in your sandbox. The second reason is control. When you connect your own E2B account, the code runs in a sandbox attached to your runtime provider account, not inside a hidden Ideavo-owned execution layer. That matters because code execution is a sensitive part of the stack. Builders should know where code is running and who controls that environment. Using your own E2B key keeps the sandbox layer closer to you. It gives you clearer ownership of the runtime, clearer billing, and a cleaner separation between the product interface and the execution environment. That is a better model than asking users to blindly trust a black-box runtime they cannot see or control. Sandbox compute selection. Not every project needs the same sandbox setup. Some projects only need a lightweight environment for everyday coding tasks. Others become heavier over time more dependencies, larger builds, more background processes, or workflows that simply need more resources to run smoothly. That is why Ideavo lets you choose the compute tier for your sandbox directly from project settings. You can select between: * Default - 4 vCPU / 4 GB RAM - a balanced setup for everyday coding tasks * Pro - 8 vCPU / 8 GB RAM - more compute for heavier, more resource-intensive workflows This becomes useful when your project gets more complex or when your sandbox starts feeling slower than usual. If your app is installing more packages, running larger builds, or handling more demanding workflows, moving to a higher compute tier gives the sandbox more room to work with.

E2B
Oct 23rd, 2025
Docker & E2B partner to introduce MCP support in E2B Sandbox

Docker & E2B partner to introduce MCP support in E2B Sandbox. Today, E2b is launching native MCP support in the E2B Sandbox. E2b has partnered with the Docker team to bring over 200+ MCP tools from the official Docker's MCP catalog to every sandbox. Watch the announcement video with Mark Cavage (President & COO at Docker), Tushar Jain (Head of Product & Engineering at Docker), and Vasek Mlejnsky (CEO at E2B). Model Context Protocol (MCP) is an open-source standard that makes it easy to connect AI systems like AI agents to external applications and use those external applications as LLM tools. In short, MCP tools make AI agents more useful and give them easy access to real world applications. However, the MCP tools can suffer from various critical security issues that can put your infrastructure at risk. Additionally, having your agents use MCP tools in sandboxes has been until now painful and required a significant amount of sandbox customization making developers spend their time on manually setting up various MCP tools and frameworks inside the sandbox instead of focusing on building the agent. E2b is bringing the MCP support to E2B sandboxes and partnering with Docker to give developers quick and easy access to hundreds of type-safe MCPs in a secure sandbox. The MCPs have been verified and are safe to consume through a single unified interface. What previously took tens of minutes to hours of setup now takes a few seconds. E2B has already been powering secure sandboxes for agent code paths, and Docker has already produced hundreds of trusted MCP servers. Together, E2b built a completely safe and trustworthy foundation for connecting AI agents with real-world tools. This partnership with Docker spans both the content collaboration and the open-source MCP gateway. Together, E2b is building on the momentum of a growing ecosystem of open, secure, and interoperable tools - while later introducing commercial extensions on top of it. The MCP tools in your E2B sandbox can be reached from both inside (accessing the MCP gateway running on localhost) and outside (via the sandbox URL), allowing your local code and sandboxed agents to share the same tools securely. import Sandbox from 'e2b' const sandbox = await Sandbox.create({ mcp: {browserbase: {apiKey: process.env.BROWSERBASE_API_KEY!, geminiApiKey: process.env.GEMINI_API_KEY!, projectId: process.env.BROWSERBASE_PROJECT_ID!,}, exa: {apiKey: process.env.EXA_API_KEY!,}, notion: {internalIntegrationToken: process.env.NOTION_API_KEY!,},}, }); import os from e2b import Sandbox sandbox = await Sandbox.create( mcp={ "browserbase": {"apiKey": os.environ["BROWSERBASE_API_KEY"], "geminiApiKey": os.environ["GEMINI_API_KEY"], "projectId": os.environ["BROWSERBASE_PROJECT_ID"],}, "exa": {"apiKey": os.environ["EXA_API_KEY"],}, "notion": {"internalIntegrationToken": os.environ["NOTION_API_KEY"],},}) MCP has become a widely adopted standard for connecting tools to LLMs. By bringing native MCP support to the E2B sandboxes, E2b is making it easy for developers and AI agents to securely access all the tools from Docker's MCP catalog such as Browserbase, Stripe, GitHub, Context7, Grafana, or Notion and make their agents more useful in just a few lines of code. Each MCP tool runs as a Docker container inside the E2B sandbox. The E2B SDK gives you autocomplete, type validation, and one unified interface to control and configure each MCP tool. How to start. Get started by installing the latest version of the E2B SDK and following quickstart examples in its documentation. Towards secure and vetted MCP tools. Its partnership with Docker allows E2b to bring many official and verified MCP servers in a secure, isolated environment. The combination of Docker's powerful MCP catalog, wide developer adoption, and its secured sandboxes make running MCP servers not only safer but also very easily accessible for all the AI developers building at the forefront of what's possible with the state-of-the-art models. E2b has given early access to the sandbox MCP support to selected of E2B users and partners. E2b want to thank Genspark, Groq, Exa, Browserbase, and others for providing valuable feedback and supporting this launcj. "E2B MCP with code unlocks an exciting paradigm of MCP in code while keeping the dev experience simple and intuitive." "Genspark uses E2B Sandbox with MCP integration to let users run 200+ MCPs from Docker's official catalog with minimal setup, giving access to tools like Notion, Stripe, Browserbase, or Exa. E2B is an essential layer in our infrastructure, enabling us to securely run any MCP directly from GitHub inside isolated sandboxes." Secure AI Sandbox

Ain.ua
Jul 28th, 2025
Czech startup E2B raises $21M Series A led by Insight Partners to scale AI agent infrastructure

Czech startup E2B raises $21M Series A led by Insight Partners to scale AI agent infrastructure.