AI System Lead Engineer

About Our Team Lenovo recently introduced Qira, a cross-device Personal AI Intelligence that works seamlessly across Lenovo and Motorola devices, creating intelligent, personalized experiences that span hardware, software, and services. Qira is a key part of Lenovo's vision to deliver AI that is contextual, proactive, and deeply integrated into everyday user experiences. We are currently hiring two System Leads to help shape the next generation of Qira capabilities: System Lead, Ambient Intelligence: Lead the design and development of ambient, always-on intelligence systems that continuously understand user context across devices and environments. System Lead, Device & Application Intelligence: Lead the development of AI-powered systems that understand and automate device and application usage patterns. Both roles offer a unique opportunity to influence the core intelligence behind Lenovo's Personal AI vision and help define how millions of users interact with AI across their digital ecosystem. Location: Onsite in Chicago, IL or San Jose, CA What You'll Do Set roadmap, milestones, and technical standards for the Ambient System team. Lead and mentor engineers across shared core and platform host work. Drive architecture decisions at trust boundaries (native ↔ shared core ↔ UI). Keep delivery predictable: clear ownership, healthy planning hygiene, early escalation Partner with product, design, security/privacy, and adjacent teams on interfaces and SLAs that support other AI capabilities and experiences Represent the team in architecture, security, and launch reviews Basic

8+ years professional software engineering experience 2+ years leading multi-engineer delivery Experience in cross-platform systems with a shared core and per-OS hosts Deep systems experience in at least two of: Rust, Kotlin/Android, Windows native, C/C++ systems Experience shipping background / always-on workloads (battery, lifecycle, scheduling, resource budgets) Experience in privacy-by-design: consent, least privilege, retention/deletion, fail-closed policy paths Experience owning API/ABI boundaries between native code and application hosts Experience delivering under launch pressure with multiple dependent teams Preferred Qualifications Multimodal sensing adjacency (screen, audio, sensors, OCR/STT, or similar signal pipelines) On-device or edge ML integration experience (inference consumers, not necessarily model training) Observability discipline: structured telemetry without leaking sensitive content Remote configuration / kill-switch patterns for production safety Consumer device, PC OEM, or mobile platform shipping experience Excellent written communication for decisions, risks, and operating cadence Familiarity with secure coding reviews and threat-aware design