Sr Engineer, Cloud AI Architect
Listed on 2026-01-17
-
IT/Tech
AI Engineer, Machine Learning/ ML Engineer
General Information
Req # WD
Career area:
Hardware Engineering
Country/Region:
United States of America
State:
North Carolina
City:
Morrisville
Date:
Wednesday, January 14, 2026
Working time:
Full-time
Additional Locations:
United States of America - North Carolina - Morrisville
We are Lenovo. We do what we say. We own what we do. We WOW our customers. Lenovo is a US $69 billion revenue global technology powerhouse, ranked #196 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 , and read about the latest news via our Story Hub.
and Requirements
Sr Engineer, Cloud AI Architect
Position Description
At Lenovo, we Never Stand Still. Every day, every employee at Lenovo is focused on moving forward, rejecting traditional limits, and always seeking a better way.
We’re looking for a Cloud AI Architect within the Global Innovation Center (GIC) Group this role As an AI and Large Language Model Architect, you will play a pivotal role in designing and implementing the technology architecture for advanced AI (including Large Language Model (LLM)) platform systems and solutions.
This role demands a skilled professional capable of designing and implementing advanced agentic AI systems that leverage both the Model Context Protocol (MCP) for contextual grounding and Agent-to-Agent (A2A) communication for seamless collaboration and task delegation between agents.
You will translate business roadmap into technical requirements and architecture. Your contributions will be instrumental in shaping cutting‑edge architectures, frameworks, and methodologies, pushing the boundaries of natural language processing (NLP) and machine learning.
You will architect sophisticated large language models (LLMs) with the remarkable ability to process and generate natural language. Additionally, you will have the opportunity to design neural network parameters, leveraging extensive amounts of unlabeled text data, to further enhance the model’s capabilities.
Role- Produce high quality architecture specifically on AI, including LLMs, Inference Engineering and Prompt Engineering and design specifications.
- Experience fine tuning an Opensource LLM
- Architect and design end to end Generative AI products, applications and solutions for specific business needs and provide implementation guidance during delivery.
- Designing and implementing autonomous AI agents capable of reasoning, planning, acting, and adapting to achieve complex objectives.
- Integrating Large Language Models (LLMs) with memory, tool‑use, and multi‑step planning architectures, leveraging their natural language understanding and generation capabilities as the agent’s "brain".
- Utilizing MCP servers or similar mechanisms to enable AI agents to interact with external enterprise applications, databases, and APIs.
- Designing and implementing agentic workflows where multiple agents communicate and collaborate using the A2A protocol to achieve shared goals.
- Analyze and evaluate the performance of Gen AI systems and provide design recommendations.
- Research, design, and implement machine learning models and algorithms, with a focus on LLM and Deep Learning techniques.
- Collaborate with cross‑functional teams to identify business problems and opportunities where machine learning solutions can add value.
- Develop and deploy scalable and…
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