Hiring: Manager, AI Engineering Company: Lenovo Location: North Carolina, United States Job Posted Time: 2026-09-12 07:41:00 Employment Type: Hybrid Target Skills & Keywords : Agile, CI/CD, Computer Vision, Docker, Fine-tuning, Git, Hugging Face, Kanban, Kubernetes, LLM, NLP, PyTorch, Python, RAG, Rust, Scrum, vLLM About the job Experience: •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) •At least 2 years of people management experience with at least 3 direct reports Required Skills: •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 Qualifications: •Master’s degree in computer science, applied math, physics, or a related field •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). •Demonstrated capacity to effectively communicate technical solutions to both technical and business audiences, both verbally and in writing •Rust experience for performance-critical inference or runtime components •Track record of collaboration with research institutions and contributions to open-source AI optimization libraries. Compensation: •Individuals may also be considered for bonus and/or commission Interested candidates, please apply directly through the job posting on company's career page or try via AI auto apply on this platform. Don't miss this opportunity to join a forward-thinking team!