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Sr. Engineer, AI Architect - - 81651
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Lenovo
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Sr. Engineer, AI Architect
General Information
Req #
WD00105132
Career area
Artificial Intelligence
Country/Region
United States of America
State
North Carolina
City
Morrisville
Date
Friday, September 11, 2026
Working time
Full-time
Additional Locations
* United States of America - California - San Jose
- United States of America - North Carolina - Morrisville
Why Work at Lenovo
We are Lenovo. We do what we say. We own what we do. We WOW our customers.
Lenovo is a US$83 billion revenue global technology powerhouse, ranked #153 in the Fortune Global 500, and serving millions of customers every day in 180 markets. Focused on a bold vision to deliver Smarter Technology for All, Lenovo has built on its success as the world’s largest PC company with a full-stack portfolio of AI-enabled, AI-ready, and AI-optimized devices (PCs, workstations, smartphones, tablets), infrastructure (server, storage, edge, high performance computing and software defined infrastructure), software, solutions, and services. Lenovo’s continued investment in world-changing innovation is building a more equitable, trustworthy, and smarter future for everyone, everywhere.Lenovo is listed on the Hong Kong stock exchange under
Lenovo Group Limited (HKSE
992) (ADR
LNVGY).
This transformation together with Lenovo’s world-changing innovation is building a more inclusive, trustworthy, and smarter future for everyone, everywhere. To find out more visit www.lenovo.com, and read about the latest news via our StoryHub.
Description and Requirements
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.
#LATC
We are an Equal Opportunity Employer and do not discriminate against any employee or applicant for employment because of race, color, sex, age, religion, sexual orientation, gender identity, national origin, status as a veteran, and basis of disability or any federal, state, or local protected class.
Additional Locations
* United States of America - California - San Jose
- United States of America - North Carolina - Morrisville
- United States of America
- United States of America - California , * United States of America - North Carolina
- United States of America - California - San Jose , * United States of America - North Carolina - Morrisville
PAY TRANSPARENCY
The anticipated annual compensation range for this position is 184,700–283,245 USD. Final compensation will be based on relevant experience, skills, and business considerations. Individuals may also be considered for bonuses and/or commissions. Lenovo’s various benefits can be found at www.lenovobenefits.com
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Skills
- Python
- PyTorch
- LLMs
- Transformer models
- Multimodal models
- Vector databases
- Knowledge graphs
- Prompt engineering
- MLOps