Head of AI Core Intelligence

This is a fully remote position, open to applicants in North Carolina.

📋 Description

• Take charge of the Core Intelligence organization, overseeing agentic systems, orchestration, routing, tool frameworks, RAG retrieval, memory, knowledge graphs, and perception signals.

• Design the intelligence layer for hybrid AI, including on-device inference, cloud fallback solutions, multi-model routing, policy enforcement, and context grounding.

• Spearhead the creation of perception-based triggers, wake-word detection logic, and understanding of screenshots and audio, as well as OCR/ASR pipelines.

• Oversee the recommendation and next-action engines, collaborating closely with Experience Engineering to deliver a contextual and proactive AI experience.

• Lead the enhancement of small and medium models (SLMs) through quantization, distillation, pruning, and tuning for specific devices.

• Work in close partnership with Platform Engineering, Cloud Platform, SRE & Delivery, and Experience teams to ensure that Core Intelligence operates efficiently, reliably, and is well-integrated.

• Establish evaluation frameworks and quality checkpoints for intelligence features, focusing on retrieval accuracy, hallucination avoidance, model grounding, and agent reliability.

• Determine the technical direction for the intelligence roadmap, balancing innovation, prototyping, and production reliability.

• Mentor senior individual contributors in areas such as perception, agentic systems, RAG, memory, and model optimization.

• Collaborate with research, product, and design teams to develop new agent capabilities and create multimodal experiences.

⛳️ Requirements

• A minimum of 12 years of engineering experience, including at least 5 years in leadership roles focusing on AI/ML systems, agent platforms, search, recommendation, or applied ML infrastructure.

• Practical experience with orchestration frameworks, agentic systems, LLM/SLM pipelines, RAG systems, embeddings, and memory architectures.

• Significant technical expertise in at least one area: perception models (OCR/ASR/vision), retrieval systems, reinforcement learning, model optimization, or distributed systems.

• Experience in developing systems that operate across devices and cloud environments, particularly in hybrid or edge contexts.

🏝️ Benefits

• Lenovo’s various benefits can be found on www.lenovobenefits.com.