Virtualization Engineer

Manus AI • Singapore • Software Development • 3d ago

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Own the architecture and core capability development of our Linux virtualization platform and MicroVM stack, with a focus on continuously improving VM startup latency, resource isolation, reliability, and security.

Responsibilities

  • Design, develop, and optimize the architecture and performance of our Linux virtualization platform.

  • Own the design, implementation, and core capability development of our MicroVM technology stack.

  • Continuously improve VM startup speed, resource isolation, reliability, and security.

Requirements

  • 5+ years of experience in Linux systems or virtualization development.

  • Deep understanding of the Linux kernel, KVM/QEMU architecture, and virtualization fundamentals.

  • Hands-on experience with MicroVM technologies such as Firecracker, Cloud Hypervisor, and Kata Containers.

  • Familiarity with at least one major cloud platform: AWS, GCP, or Azure.

  • Strong proficiency in C/C++, Rust, or Go, with solid system debugging and performance profiling skills.

  • An experienced Code Agent user who can effectively leverage AI coding tools for complex systems development, debugging, and code review.

  • Ability to conduct in-depth technical collaboration in Chinese, and to read, write, and participate in day-to-day technical communication in English.

Preferred Qualifications

  • Upstream contributions to open-source projects such as the Linux kernel, KVM, QEMU, Firecracker, Cloud Hypervisor, Kata Containers, or rust-vmm.

  • Core engineering experience on compute or virtualization teams at a major cloud provider, with production experience operating large-scale VM or MicroVM clusters.

  • Deep optimization experience in areas such as VM snapshot and restore, live migration, memory overcommit and deduplication, device passthrough, virtio, or vhost-user.

  • R&D experience related to AI Agent sandboxes, Serverless infrastructure, or secure container technologies such as E2B or gVisor.

  • Open-source projects, technical publications/blogs, or equivalent non-public engineering accomplishments that demonstrate strong systems expertise.

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