Nvidia Ai Solution Architect

**General Information**:

- Req #
- WD00082803
- Career area:

- Artificial Intelligence
- Country/Region:

- Germany
- City:

- Stuttgart
- Date:

- Wednesday, May 21, 2025
- Working time:

- Full-time

**Additional Locations**:

- Germany

**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$57 billion revenue global technology powerhouse, ranked #248 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).

**Description and Requirements**:

- We are looking for an AI Delivery Architect / Technical lead who can understand the AI solution requirements to design, deploy, tested and validate - Proof of Concepts (PoCs) and full production environments for enterprise customers. This role focuses on the end-to-end deployment design, working closely with customer c-suite team, understand use case and create AI solution. Create detailed deployment solution covering infra, software, tools, process, and procedures that include Nvidia AI Enterprise solutions on Lenovo hardware and ensuring seamless, scalable, and robust production implementations. Your work will help customers unlock the full potential of AI technologies by managing deployments that ensure AI adoption and optimization of AI models in real-world use cases.

**Key responsibilities**:

- Lead end-to-end transitions of AI PoCs into production environments, managing the entire process from testing to final deployment.
- Configure, install, and validate AI systems using key platforms, including:

- VMware ESXi and vSphere for server virtualization, Linux (Ubuntu/RHEL) and Windows Server for operating system integration, Docker and Kubernetes for containerization and orchestration of AI workloads.
- Conduct comprehensive performance benchmarking and AI inferencing tests to validate system performance in production.
- Optimize deployed AI models for accuracy, performance, and scalability to ensure they meet production-level requirements and customer expectations.
- Serve as the primary technical lead/SME for the AI POC deployment in enterprise environments, focusing on AI solutions powered by Nvidia GPUs.
- Work hands-on with Nvidia AI Enterprise and GPU-accelerated workloads, ensuring efficient deployment and model performance using frameworks such as PyTorch and TensorFlow.
- Lead technical optimizations aimed at resource efficiency, ensuring that models are deployed effectively within the customer’s infrastructure.
- Implement risk management strategies and develop contingency plans to mitigate potential issues such as hardware failures, network bottlenecks, and software incompatibilities.
- Maintain ongoing, transparent communication with all relevant stakeholders, providing updates on project status and addressing any issues or changes in scope.
- Conduct post-deployment knowledge transfer sessions to educate client/ Lenovo Managed services teams on managing AI infrastructure, troubleshooting common issues, and optimizing AI models.
- Provide comprehensive training sessions on the operation, management, and scaling of AI systems, ensuring that customers are fully prepared for ongoing operations post-handoff.

**Experience**:

- Overall experience 7-10 years
- Relevant experience of 2-4 years in deploying AI/ML models/ AI solutions using Nvidia GPUs in enterprise production environments.
- Demonstrated success in leading and managing complex AI infrastructure projects, including PoC transitions to production at scale.

**Technical Expertise**:

- Experience in the area of Retrieval Augmented Generation (RAG), NVIDIA AI Enterprise, NVIDIA Inference Microservices (NIMs), NVIDIA NeMo framework, Model Management, Kubernetes
- Extensive experience with Nvidia AI Enterprise, GPU-accelerated workloads, and AI/ML frameworks such as PyTorch and TensorFlow.
- Proficient in deploying AI solutions across enterprise platforms, including VMware ESXi, Docker, Kubernetes, and Linux (Ubuntu/RHEL) and Windows Server environments.
- MLOps proficiency with hands-on experience using tools such as Kubeflow, MLflow, or AWS SageMaker for managing the AI model lifecycle in production.
- Strong understanding of virtualization and containerization technologies to ensure robust and scalable deployments.

**What Lenovo can offer you**:

- Employee Share Purchas