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 - Baden-Württemberg - Stuttgart
• Germany - Baden-Württemberg - Stuttgart

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.

WHAT LENOVO CAN OFFER YOU:

• Employee Share Purchase Plan
• Employee Assistance Program, e.g., for health, legal & financial consultancy
• Pension Plan
• Meal Allowance / Lunch Vouchers
• Internal E-learning Development Platform Available for Employees
• Specialized Development Trainings (based on nomination process)
• Employees Groups (LGBT+, WILL, etc.)
• Opportunity to Join/Create Employees Groups (inclusivity, well-being, sports, volunteering, charity, etc.)
• Job Rad (Bike Leasing)
• Mobile phone + 3 Sim Cards for Mobile Working
  Check out the video, our DACH team created, to give you an insight into the Lenovo culture! We are looking forward to talking to you!
  Youtube Video
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  At Lenovo, we are proud to be an equal opportunities company. Of course, this also applies to people with disabilities.
  When applying for this position, please send your CV (including covering letter and references) via our Online-Tool. At Lenovo we are proud to be an equal opportunity company. This vacancy certainly applies for people with disabilities too.

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

• 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.