Senior Solutions Architect, AI Cloud Services
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Job Description
Solutions Architect helping customers deploy NVIDIA AI software and hardware on cloud GPU platforms. Building scalable solutions, proofs of concept, and technical partnerships for enterprise customers.
Responsibilities:
- Work with Cloud Service Providers to develop and demonstrate solutions based on NVIDIA software and hardware technologies
- Build and deploy solutions at scale using NVIDIA AI software on cloud-based GPU platforms
- Build custom proofs of concept addressing customers’ critical business needs with NVIDIA technologies
- Partner with Sales Account Managers or Developer Relations Managers to identify and secure business opportunities
- Conduct technical customer meetings covering project and product details, feature discussions, new technologies, and debugging
- Prepare and deliver technical customer content, including presentations and workshops
- Serve as the first line of technical expertise between NVIDIA and customers
- Engage developers, researchers, and data scientists
- Work closely with business and engineering on product strategy
- Drive end-to-end technology solutions incorporating NVIDIA’s full technology stack
Requirements:
- BS, MS, PhD in Electrical/Computer Engineering, Computer Science, Physics, or another Engineering field, or equivalent experience
- 4+ years of Solutions Engineering or similar Sales Engineering experience
- Track record of deploying AI/ML solutions in cloud environments, including AWS, GCP, Azure, or OCI
- Knowledge of DevOps/MLOps technologies such as Docker/containers, Kubernetes, and data center deployments
- Effective time management and ability to balance multiple tasks
- Ability to communicate ideas clearly through documents and presentations
- AWS, GCP, Azure, or OCI Professional Solutions Architect certification is a preferred differentiator
- Hands-on experience with NVIDIA GPUs and SDKs such as CUDA, Triton, and TensorRT-LLM is preferred
- Deep understanding of the software development lifecycle, system design, architectural patterns, and comprehensive testing is preferred
- Solid working knowledge of Python is preferred
- System-level experience with GPU-based systems is preferred
- Occasional travel required for local customer visits and industry events
Benefits:
- Equity
- Benefits
- Remote work locations
- Occasional travel for local on-site visits to customers and industry events
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