Lenovo

Job Descriptions:

• Build trusted relationships with Sales, C-level executives, and technical decision makers to ensure early engagement in customers’ AI strategy and solution discussions.
• Represent Lenovo Solutions & Services Group (SSG) during the sales cycle, including project scoping, solution architecting, proposal development, effort sizing and pricing, plus presentation - supporting NVIDIA-based AI stack, Generative AI, and AI infrastructure opportunities.
• Ensure that customer expectations around AI capabilities, timelines, and outcomes are realistically set and managed.
• Facilitate GenAI, LLM, and AI strategy discovery workshops to surface business use cases and technical readiness.
• Lead technical advisory and solutioning efforts in presales, including sizing of infrastructure and services based on NVIDIA’s AI stack, with a warm handover to deliver upon deal closure.
• Strong capability in both AI solution architecture and presales services estimation (including training, tuning, deployment, and MLOps components).
• Serve as a technology thought leader and internal evangelist for AI adoption and customer success.
• Assist in building and leveraging an internal and external partner ecosystem, including NVIDIA, to craft end-to-end AI solutions spanning infrastructure, software, services, and MLOps pipelines.
• Maintain up-to-date knowledge of AI trends, including NVIDIA AI Enterprise stack, open-source tools, and cloud-native AI/ML platforms.
• Stay current through certification and enablement in relevant AI technologies (e.g., NVIDIA Certified, Azure/AWS/GCP AI services, MLOps frameworks).
• Contribute to the development of internal solution capabilities and customer-facing collateral when required.

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.
• Act as AI advocate internally and externally, participating in thought leadership, enablement, and customer education sessions.
• Any other responsibilities allocated by management.

Basic Qualifications:

• 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).
• Excellent communication, documentation, and interpersonal skills across culturally diverse teams.
• Ability to travel for customer workshops and events as required.

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.
• Strong self-learning aptitude with a proactive and customer-first mindset.