Consulting Researcher Hardware Security Expert – Low Level / Embedded AI Systems

We are Lenovo. We do what we say. We own what we do. We WOW our customers.

Lenovo is a US$69 billion revenue global technology powerhouse, ranked #196 in the Fortune Global 500, and serving millions of customers every day in 180 markets. Focused on a bold vision to deliver Smarter Technology for All, Lenovo has built on its success as the world’s largest PC company with a full-stack portfolio of AI-enabled, AI-ready, and AI-optimized devices (PCs, workstations, smartphones, tablets), infrastructure (server, storage, edge, high performance computing and software defined infrastructure), software, solutions, and services. Lenovo’s continued investment in world-changing innovation is building a more equitable, trustworthy, and smarter future for everyone, everywhere. Lenovo is listed on the Hong Kong stock exchange under Lenovo Group Limited (HKSE: 992) (ADR: LNVGY).

This transformation together with Lenovo’s world-changing innovation is building a more inclusive, trustworthy, and smarter future for everyone, everywhere. To find out more visit www.lenovo.com, and read about the latest news via our StoryHub.

Lenovo Digital Trust Lab is looking for a Hardware Security Expert Low Level to focus on securing the embedded and hardware layers of AI pipelines and agentic systems. This role will bring deep expertise in low-level security (firmware, trusted execution, hardware roots of trust) to ensure that our models, data, and orchestration cannot be compromised at the device or infrastructure layer.

You will design, test, and deploy hardware-anchored protections for AI workloads across edge, device, and hybrid environments, and partner with researchers to integrate them into Lenovos products and AI ecosystem.

Job Responsibilities

• Design and implement low-level security mechanisms for AI devices and pipelines (secure boot, trusted execution environments, hardware attestation).
• Research and deploy hardware-anchored model protection techniques, including model encryption, signing, and integrity validation.
• Conduct firmware and hardware security testing to identify risks such as tampering, side-channel leakage, or privilege escalation.
• Develop prototypes for secure AI at the edge, ensuring privacy, integrity, and resilience in device-level inference.
• Collaborate with software and AI teams to integrate hardware controls into the broader Hybrid AI Security stack.
• Build internal tooling for simulation and testing of hardware threats, including malicious firmware, compromised drivers, and physical attacks.
• Track developments in TPM, TEEs, SEs, and hardware security modules, and evaluate their application to agentic AI orchestration.