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E2B

Cloud-based sandboxed AI development platform

Platform Engineer

Platform EngineeringUpdated on Nov 12
Full-timeSan Francisco, CA, USA$250k - $350k /yr

About the Job

Requirements

  • At least 5 years of building distributed systems and experience operating infrastructure at serious scale, including 100K+ requests per second, multi-region, or petabyte-scale data, with practical understanding of consistency, availability, and partition tolerance trade-offs.
  • Deep Linux internals expertise, including kernel-level work, debugging performance with eBPF, CPU scheduling, memory management, and cgroups v1 and v2.
  • Experience with VM hypervisors such as Firecracker, QEMU, or KVM; understanding of virtio, hypercalls, and nested virtualization trade-offs.
  • Strong systems programming skills in at least one of Go, Rust, C, or C++; experience writing performance-critical code and using lock-free data structures, memory-mapped files, or io_uring where appropriate.
  • Production experience building or operating orchestration systems such as Kubernetes, Nomad, or custom systems; understanding of bin-packing algorithms and resource scheduling, and experience addressing noisy-neighbor problems at scale.
  • Experience profiling production systems under load and optimizing performance, including CPU caches, memory locality, and p99 latency.
  • Strong networking knowledge, including L4/L7 load balancing, network namespaces, iptables or nftables, and secure, isolated network topologies for multi-tenant systems.
  • Located in San Francisco or willing to relocate; able to work in person with the team.
  • Comfort working with public open-source code and infrastructure, contributing to discussions, writing documentation, and supporting self-hosting.

Responsibilities

  • Build a distributed system for millions and billions of AI agents running on the platform.
  • Build an orchestrator that places sandboxes on appropriate nodes.
  • Add support for live migration of sandboxes.
  • Improve the self-hosting developer experience for the open-source platform.
  • Keep sandbox startup time under 200 milliseconds, measured from the user initiating the action.
  • Scale the platform to run millions and eventually billions of sandboxes simultaneously.
  • Build an observability stack starting at the virtual machine kernel level.

Desired Qualifications

  • Experience with userfaultfd (UFFD), copy-on-write mechanisms, or lazy loading.
  • GPU passthrough or PCIe device virtualization experience.
  • Experience building or maintaining infrastructure for AI or machine-learning workloads.
  • Contributions to Firecracker, Cloud Hypervisor, or similar open-source projects.
  • Experience with observability at scale, including distributed tracing or kernel-level metrics.

About the Company

E2B

Cloud-based sandboxed AI development platform

E2B provides cloud-based development tools for AI developers, with a focus on large language model applications. Its main offering is a ChatGPT plugin that connects to a full sandboxed cloud environment running on E2B’s own infrastructure. The product works by integrating with ChatGPT’s code interpreter to give developers a secure workspace where they can write, test, and run AI-driven code, with memory, security, data privacy, and testing handled by the platform. E2B differentiates itself through a tightly integrated, cloud-backed development environment centered on a secure sandbox and developer-focused tooling, rather than generic cloud services. The company aims 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, CA
Founded
2023

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