Sr. Engineer, AI Architect

Summary: 

Lenovo is seeking a highly experienced and visionary Sr. AI Architect to lead the design and implementation of our next-generation AI systems. This is a pivotal role responsible for the overall technical direction, architecture, and scalability of our AI platform. The ideal candidate is a deep generalist with a comprehensive understanding of the entire AI stack – from foundational models to application-level agents – and the ability to articulate complex technical concepts to both technical and non-technical audiences. You will be one of the go-to experts for all things AI, guiding engineering teams and driving innovation in a rapidly evolving field. If you are passionate about making Smarter Technology For All, come help us realize our Hybrid AI vision! 

Responsibilities: 

• System Architecture: Design and maintain the overall architecture of our AI systems, ensuring scalability, reliability, and performance. 

• Model Expertise: Possess in-depth knowledge of a wide range of AI models, including Large Language Models (LLMs), multimodal models (vision, speech, text), and their underlying principles. 

• Training & Fine-tuning: Architect and oversee the training and fine-tuning of AI models, including techniques like Supervised Fine-Tuning (SFT), LoRA (Low-Rank Adaptation), and prompt tuning. 

• Agent Design: Lead the design and implementation of intelligent agents, encompassing components like intent understanding, task decomposition and planning, and tool calling (e.g., using MCP – Model Context Protocol). 

• Knowledge Management: Design and implement robust knowledge management systems, including vector databases, reranking models and algorithms, and knowledge graphs. 

• Output Optimization: Select output sampling strategies to ensure high-quality, relevant, and coherent responses. 

• Technical Leadership: Provide technical leadership and mentorship to engineering teams, guiding them through the implementation of complex AI solutions. 

• Research & Innovation: Stay abreast of the latest advancements in AI research and identify opportunities to apply them to our products and services. 

• Cross-Functional Collaboration: Work closely with product management, data science, and engineering teams to define requirements and deliver innovative AI solutions. 

• System Documentation: Create and maintain comprehensive documentation of the AI system architecture and components. 

Required Qualifications: 

• Advanced degree (Ph.D. preferred) in Computer Science, Artificial Intelligence, or a related field. 

• 12+ years of experience designing and implementing AI systems. 

• Understanding of Machine Learning and Deep Learning principles. 

• Extensive experience with Large Language Models (LLMs) and Transformer architectures. 

• Hands-on experience with multimodal models. 

• Proficiency in programming languages such as Python. 

• Experience with Machine Learning frameworks such as PyTorch. 

• Strong understanding of vector databases and embedding models. 

• Experience with knowledge graphs and knowledge base management. 

• Familiarity with prompt engineering techniques and prompt optimization. 

Preferred Qualifications: 

• Experience with MLOps practices and deploying AI models to production. 

• Contributions to open-source AI projects. 

• Publications in leading AI conferences or journals. 

• Familiarity with Atlassian tools (Jira, Confluence)

• Excellent communication, interpersonal, and presentation skills, including clear descriptions and document generation, such as class diagrams, sequence diagrams, and protocol definitions.