Lenovo

*Please Note: This role will be hybrid with 3 days/week in office in Morrisville, NC*

Lenovo AI Technology Center (LATC) Overview

The Lenovo AI Technology Center (LATC) is Lenovo’s global AI Center of Excellence, driving the company’s transformation into an AI-first organization. LATC builds and operates core AI platforms and technologies that enable intelligent experiences across Lenovo’s full product portfolio, spanning devices, edge, and cloud. Working in close partnership with Lenovo’s business groups and product teams, LATC translates advanced AI innovation into scalable, production-ready capabilities that power real-world products and solutions. 

About the Role

We are looking for a technical and people leader of a team of engineers and scientists who own the full agentic stack — from LLM orchestration, tool use, memory, and production deployment. 

Responsibilities

• Lead and mentor a team of engineers and scientists working on agentic workflows that work on-device, across-device, and on-cloud.
• Lead cross-functionally to set technical direction, prioritize projects, and ensure timely delivery of high-quality outcomes.
• Foster collaboration across globally distributed engineering teams and organizations.
• Design and ship agentic LLM pipelines: multi-step reasoning, tool use, reflection loops, and long-horizon planning and memory
• Build evaluation frameworks to measure agent reliability and safety across different tasks.
• Build and maintain RAG systems, vector stores, and external tool integrations
• Deploy and scale agent systems in production; translate relevant research into working systems
• Be a technical lead, working closely with other AI engineers, ML scientists, and technical product managers to put pipelines in production
• Keep abreast of the latest developments in AI & ML, applying cutting-edge research and methodologies to your work

Required Qualifications

• At least 2 years of people management experience with at least 3 direct reports
• 6 years of industry experience in ML or applied AI with strong hands-on LLM experience (prompting, fine-tuning, inference optimization)
• Master’s degree in computer science, applied math, physics, or a related field
• Experience with NLP
• Fluent in Python and the modern ML stack (PyTorch, Hugging Face, vLLM or equivalent)
• Proven experience with agentic frameworks (LangGraph, AutoGen, CrewAI, or custom), tool-use patterns (function calling, MCP, structured outputs), and human-in-the-loop mechanisms
• Solid grasp of RAG architecture, embedding models including multimodal embeddings, and LLM evaluation methodology
• Strong software engineering fundamentals (python and at least one other programming language).
• Experience with Git, and Continuous Integration/Continuous Deployment (CI/CD)
• Experience deploying ML models using containerization and container orchestration technologies such as Docker and Kubernetes
• Ability to effectively communicate technical solutions to both technical and business audiences, both verbally and in writing
• Experience with Agile frameworks, such as Scrum and Kanban

Preferred Requirements

• PhD
• Experience with computer vision
• Rust experience for performance-critical inference or runtime components
• Track record of collaboration with research institutions and contributions to open-source AI optimization libraries.

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