AI Infrastructure Architect: GPU & Datacenter

Lenovo; North Carolina; On-site; USD 170,000 - 250,000; Full time

Job summary

Lenovo is seeking a Senior Solution Architect to lead GPU-powered, datacenter-scale AI infrastructure. You will architect platforms that power ML workloads and define deployment frameworks, while collaborating with engineering and customers to deliver production-ready solutions.

Ideal candidates bring 8+ years in datacenter systems, strong programming in Python/C++/Go, and practical ML/DL knowledge with PyTorch.

Qualifications

• BS/MS in Computer Science, Computer Engineering, Electrical Engineering, or related field.
• 8+ years building and scaling datacenter systems (servers, networking, storage, or performance).
• Strong programming skills in Python, C/C++, Go, and systems thinking.
• Working knowledge of ML/DL concepts and frameworks (PyTorch, LangChain, Autogen).
• Proven ability to operate in fast-paced, ambiguous environments and deliver impact.

Responsibilities

• Architect end-to-end AI infrastructure solutions at rack and datacenter level.
• Define deployment frameworks, tooling, and methodologies for AI cluster bring-up and optimization.
• Drive hardware/software innovation to improve performance, scalability, and reliability.
• Partner across engineering, product, and customers to deliver production-ready AI solutions.
• Influence solution strategy through hands-on design, benchmarking, and customer engagement.

Skills

Python

C/C++

Go

Machine learning concepts

PyTorch

Education

BS/MS in Computer Science, Computer Engineering, Electrical Engineering, or related field

Tools

PyTorch

LangChain

Autogen

Job description

Lenovo is seeking a Senior Solution Architect to lead GPU-powered, datacenter-scale AI infrastructure. You will architect platforms that power ML workloads and define deployment frameworks, while collaborating with engineering and customers to deliver production-ready solutions.

Ideal candidates bring 8+ years in datacenter systems, strong programming in Python/C++/Go, and practical ML/DL knowledge with PyTorch.