AI Infrastructure Engineer, Sandbox Platform

About the Role

As a Software Engineer on the AI Infrastructure team, you'll help build and evolve our agent sandboxing platform — the secure, high-performance code execution layer powering our agentic workflows, deployed across both internal and customer-managed environments. This is a role for someone who cares as much about the experience of the engineers and researchers using this system as they do about the kernel internals underneath it.

What You'll Do

• Design and build the sandboxing platform, client library, and API surface for secure code execution across containerized and virtualized environments.
• Ensure strong isolation, security, and reproducibility of execution across user sessions and workloads.
• Optimise for cold-start latency, memory footprint, and resource utilisation at scale.
• Drive down error rates through systematic debugging, monitoring, and proactive fixes.
• Partner closely with internal teams using the platform to understand their needs, debug issues, and build tooling that serves their use cases.
• Respond to incidents and production issues with urgency, conducting root cause analysis and implementing preventive fixes.
• Help develop and maintain a product roadmap for sandboxing, balancing immediate needs against long-term architectural investment.
• Lead architecture reviews and own projects end-to-end, from design through deployment, in fast-paced cross-functional settings.

Who You Are

• 4+ years of experience building high-performance systems software, with meaningful time spent maintaining libraries, SDKs, or developer-facing APIs.
• Deep understanding of Linux internals: process isolation, memory management, cgroups, namespaces, etc.
• Experience with containerisation and virtualisation technologies (e.g., Docker, Firecracker, gVisor, QEMU, Kata Containers).
• Proficiency in a systems programming language such as Go, Rust, or C/C++.
• A track record of obsessing over developer experience — API design, error propagation, documentation, and the small details that make a library feel well-crafted.
• Comfort working across infrastructure layers, from kernel modules to orchestration frameworks (e.g., Kubernetes).
• Strong debugging skills and the ability to navigate performance/security tradeoffs in production systems.
• Comfort with ambiguity, and the ability to context-switch between reactive incident work and proactive product development.

Bonus Points

• Experience as a founder or early engineer at an infrastructure-focused startup, owning a product end-to-end.
• Familiarity with LLM agents and agent frameworks (e.g., OpenHands, Agent2Agent, MCP).
• Experience running secure workloads in multi-tenant or untrusted environments (e.g., FaaS, CI sandboxes, remote notebooks).
• Exposure to snapshotting and restore techniques (e.g., CRIU, VM snapshots, overlays).
• Open-source contributions to systems or developer-tools projects.
• History of on-call/incident response for production systems.

Compensation

Please note: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants.

About Us

At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact.