nVidia AI Solution Architect

Full Description

Lenovo AI Solutions Architect Job Description

We are seeking a skilled and experienced AI solutions architect to join our team at Lenovo.

This is an exciting opportunity to work with cutting-edge AI technology and collaborate with top clients in the industry.

Responsibilities:

• Lead AI discovery sessions and technical/roadmap workshops with clients to understand pain points, use cases, and success criteria.

• Architect end-to-end AI solutions using NVIDIA's AI stack (e.g., Base Command, DGX, NeMo, Triton, TensorRT, NGC, RAPIDS, CUDA, AI Enterprise) and supporting technologies (e.g., Kubernetes, Kubeflow, MLFlow).

• Scope, size, and price AI services—including infrastructure sizing, LLM customization, fine-tuning, inference optimization, and MLOps pipelines.

• Create solution documentation such as technical write-ups, architecture diagrams, proposal content, and scope of work (SOW).

• Lead internal Solution Certification processes and ensure compliance with internal presales workflows.

• Support transition to delivery through a structured and warm handover process.

• Collaborate closely with offering, delivery, and marketing teams to refine offerings and support go-to-market activities.

Key Requirements:

• 10+ years of experience in enterprise IT, with at least 3–5 years in AI/ML architecture, data science solutioning, or AI platform engineering.

• Deep understanding of NVIDIA's full AI stack and ecosystem, including DGX platforms, AI Enterprise Suite, Base Command, NeMo, Triton Inference Server, and TensorRT.

• Strong experience in GenAI/LLM concepts, including prompt engineering, fine-tuning, vector databases, inference optimization, and ethical AI governance.

• Demonstrated experience designing AI pipelines on-premises and in cloud environments (e.g., Azure AI, AWS Sagemaker, GCP Vertex AI).

• Proven ability to translate business requirements into scalable technical architectures and present to both technical and business stakeholders.

• Strong experience in pricing and effort estimation of AI services, including hardware sizing and GPU-based workload planning.

• Hands-on experience with Python-based AI frameworks and orchestration tools (e.g., PyTorch, TensorFlow, Hugging Face, MLFlow, Kubernetes).

Preferred Qualifications:

• NVIDIA Certified AI Specialist or similar AI certifications (Azure AI Engineer, AWS Machine Learning Specialty, etc.).

• Experience with open-source LLM platforms (e.g., Llama, Mistral, Falcon), vector DBs (e.g., FAISS, Weaviate), and retrieval-augmented generation (RAG).

• Familiarity with MLOps frameworks and responsible AI practices.

• Prior experience in AI consulting or AI pre-sales roles with demonstrable deal wins.

• Knowledge of AI trends and applications across industries (e.g., finance, healthcare, manufacturing).

• Fluency in English, with additional regional language proficiency in Asia Pacific as an advantage.