Platform Engineer
Company websitee2b.dev (E2B, opens in new tab)
Base salary $250K to $350K
Employer-published annual base salary, USD. Advertised base range in San Francisco, CA
You apply on the employer's own site. Six Figure Work does not handle applications.
- LocationSan Francisco, CA
- WorkplaceOn-site
- Status at last checkSource accepting applications when checked
- Last checked (2 h ago) · observed since
About this job
About E2B
E2B is a fast-growing Series A startup with over $37M in funding and 8-figure revenue. We are building the Agent Cloud and power the infrastructure behind AI labs and some of the most widely used consumer and enterprise agents, including Manus, Genspark, Lindy, Groq, and Artificial Analysis. Our team includes original authors of Firecracker, the AWS microVM technology powering Lambda, along with alumni of Cognition, JetBrains, Zapier, and Wish.
About the role
You will be building the next cloud platform for running AI software - a cloud where AI apps are building other software apps.
Your job will be:
Building a distributed system for millions and billions of AI agents running on E2B
Building an orchestrator for placing sandboxes in the right nodes
Adding support for sandbox live migrations
Making sure our self-hosting DX is as smooth as possible (we’re open-source)
Not letting our sandboxes take more than 200ms to start (starting with the user hitting enter)
Scaling to millions and later billions of sandboxes running at the same time
Building an observability stack starting at the kernel level of virtual machines
We’re looking for an infrastructure engineer passionate about making things run fast and efficiently, and running A LOT of them at the same time.
If you aren’t afraid of going into the kernel of a VM and words like Firecracker, eBPF, UFFD, block device, L4 load balancing, noisy neighbor problem, or hugepages sound exciting to you, we want to hear from you!
What we're looking for
5+ years building distributed systems - You've operated infrastructure at serious scale (100K+ RPS, multi-region, PB-scale data) and understand the trade-offs between consistency, availability, and partition tolerance in practice, not just theory
Deep Linux internals expertise - You're comfortable working at the kernel level. You've debugged performance issues using eBPF, understand CPU scheduling, memory management, and can explain the difference between cgroups v1 and v2 without looking it up
VM hypervisor experience - You've worked with Firecracker, QEMU, KVM, or similar. You understand virtio, know what a hypercall is, and have opinions about nested virtualization trade-offs
Systems programming skills - Strong in at least one of: Go, Rust, C/C++. You've written performance-critical code and know when to reach for lock-free data structures, memory-mapped files, or io_uring
Production orchestration experience - You've built or operated orchestration systems (Kubernetes, Nomad, or custom). You understand bin-packing algorithms, resource scheduling, and have dealt with noisy neighbor problems at scale
Performance obsession - You've shaved milliseconds off hot paths, understand CPU caches and memory locality, and have profiled production systems under load. You know what "p99 latency" means and care deeply about making it better
Networking expertise - Strong understanding of L4/L7 load balancing, network namespaces, iptables/nftables, and how to build secure, isolated network topologies for multi-tenant systems
Located in San Francisco or willing to relocate - We work in person as a team and believe in the magic that happens when engineers collaborate face-to-face on hard problems
Excited about open source - Comfortable with our code and infrastructure being public. You contribute to discussions, write clear documentation, and help the community succeed with self-hosting
Bonus points for:
Experience with userfaultfd (UFFD), copy-on-write mechanisms, or lazy loading
GPU passthrough or PCIe device virtualization experience
Built or maintained infrastructure for AI/ML workloads
Contributions to Firecracker, Cloud Hypervisor, or similar open source projects
Experience with observability at scale (distributed tracing, kernel-level metrics)
What it’s like to work at E2B
We’re a fast-growing startup with in-person (4 days on-site, 1 day WFH) offices in San Francisco and Prague, Czech Republic. We already generate 8-figure revenue and work directly with top-tier AI companies like Manus, Genspark, Lindy, Groq, Artificial Analysis and other exciting teams pushing the frontier of AI.
We offer healthcare, vision, and dental insurance, unlimited PTO, 401k, and a variety of perks for in-office employees.
Source: E2B on Ashby · View original posting (opens in new tab)
This listingPlatform Engineer$250K to $350K
Senior Data Engineer$200K to $250K
Business Operations$200K to $230K
Product Engineer - Backend Developer$175K to $350K
Founding Product Marketing Lead$170K to $230K
Founding Community & Ecosystem Lead$170K to $230K
Technical Recruiter$150K to $250K
Chart as a table
| Role | Published base |
|---|---|
| Platform Engineer (this listing) | $250K - $350K |
| Senior Data Engineer | $200K - $250K |
| Business Operations | $200K - $230K |
| Product Engineer - Backend Developer | $175K - $350K |
| Founding Product Marketing Lead | $170K - $230K |
| Founding Community & Ecosystem Lead | $170K - $230K |
| Technical Recruiter | $150K - $250K |
Observed changes
- Began meeting the published-salary criteria
- First observed on the employer's board
- Observed since
- Employer-stated posting date
- 2025-09-29
Where this pay comes from
Location as the employer wrote it: San Francisco
USD 250,000 – 350,000 · 1 YEAR · Salary
- Method
- Structured pay field published by the employer
- Checked
- Rule set
- us-base-v2
The employer's job board publishes this pay as a dedicated data field. We read the field directly; no interpretation was needed.
What we verified
- The pay figures come from the employer's own listing, quoted exactly above.
- The pay is an annual base salary in US dollars with a minimum of at least $100,000.
- The role was publicly listed on the employer's job board when last checked.
We do not verify what the employer will actually offer, whether the employer is still recruiting for the role, or anything beyond what the employer published. Full methodology.
