E2B operates a cloud platform purpose-built for running AI agent software in isolated, monitored sandboxes. The stack is infrastructure-heavy—Firecracker, gVisor, eBPF, seccomp, Kubernetes, Nomad—reflecting a focus on kernel-level isolation and observability. Engineering dominates the 11-50 person org, with acute pain points around sandbox performance, latency, and threat detection at scale, suggesting they're handling production workloads with strict SLO requirements.
Tech Stack 34 technologies
Core StackNext.js TypeScript Python LangChain Go Rust Linux Ruby Kubernetes Nomad Terraform React Supabase PostgreSQL Figma Adobe Illustrator After Effects LlamaIndex Haystack C Firecracker eBPF seccomp gVisor QEMU KVM C/C++ WebSockets Photoshop iptables+4 more
What E2B Is Building
◆Challenges
- Optimizing sandbox performance
- Scaling to millions of sandboxes
- Scaling brand identity
- Securing billions of ai agents
- Maintaining sub-200ms performance
- Real-time threat detection at scale
- Secure isolated environments
- Reducing sandbox start latency
- Observability at kernel level
- Solving general infrastructure challenges at scale
▲Active Projects
- Building the next cloud platform for running ai software
- Cookbook
- Observability stack
- Fragments
- Ai analyst
- Sandbox orchestrator
- Large-scale campaigns in cities like san francisco and prague
- Designing and building the e2b backend and core infrastructure
- Building and optimizing runtimes and sandboxes for llms
- Visual identity across digital and physical channels
Hiring Activity
15 roles · 4 in 30d
Department
Seniority
Company intelligence
