Director, AI OS - REMOTE

* United States of America - North Carolina - Morrisville

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Lenovo is building a new AI layer that lives natively on devices – closer to the OS than to any single app. As Director, AI OS , you will lead the team responsible for the system software and runtime layer that AI features run on across PCs and other devices.

This is a system-level engineering leadership role for someone who has built operating systems or core system software before (kernel, runtime, system services, device frameworks, or similar), and now wants to apply that experience to AI.

You will design and own the AI OS layer that provides:

lifecycle, scheduling, and runtime for AI workloads

access to device capabilities (audio, display, sensors, file system, network, NPU, GPU, etc.)

a safe and performant “computer use” abstraction for agents

the system substrate that exposes and integrates latent-space representations, planning and predictive engines

Define and own the architecture of the AI OS layer on Lenovo devices, including runtime services, process/lifecycle management for AI workloads, and integration with existing OS subsystems.

Design and evolve the AI OS runtime so that AI features can run efficiently, safely, and predictably on-device, across multiple device classes.

Provide abstractions for “computer use” – how AI systems can safely interact with windows, applications, files, and other system resources.

Work with Core Intelligence to ensure the OS runtime can host and expose latent-space representations , and integrate with planning and predictive engines that sit above it.

Own the device API surface for AI: sensors, audio, display, input, power, storage, network, and NPU/GPU/CPU acceleration.

Ensure that high-fidelity signals and state from the OS (usage context, app state, input/output streams) can be routed into Core Intelligence and the latent space in a controlled way.

Work closely with hardware, firmware, and OS teams to ensure AI workloads can take full advantage of device capabilities without compromising stability or security.

Bring deep system experience (kernel / drivers / system services / frameworks) to decisions about where AI logic lives – on-device vs cloud, OS layer vs app layer.

Make tradeoffs between performance, power, privacy, and maintainability, and ensure those tradeoffs are visible and understood by other leaders.

Work closely with SRE & Delivery Engineering on how AI OS is instrumented, observed, and upgraded over time (especially as latent-space and agent workloads evolve).

Build and lead a team of engineers focused on AI OS runtime, computer use, device APIs, and full-stack OS integration.

Mentor engineers in system design, reliability, and quality best practices for OS-level software.

Collaborate closely with leaders of Platform Services, Core Intelligence, Experience…