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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Solutions Architect, AI Cloud Services - **Company:** NVIDIA Ltd. - **Location:** New York, NY, United States (Remote available) - **Experience:** Expert - **Salary:** $152,000.0 - $287,500.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, Architectural Patterns, Microsoft Azure, Cloud Computing, Nvidia CUDA, Computer Engineering, Data Centers, Software Debugging, DevOps, Python (Programming Language), Machine Learning, Cloud Services, Software Engineering, System Testing, Graphics Processing Unit (GPU), Google Cloud, Cloud Platform System, Large Language Models, Build Management, Kubernetes, Information Technology, Machine Learning Operations, TensorRT, Hardware Infrastructure, Oracle Cloud Infrastructure, Docker - **Published:** May 14, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=4ddc540f153855ff ## About the Role Do you have experience in MLOps?, * BS/MS/PhD in Electrical/Computer Engineering, Computer Science, Physics, or other Engineering fields or equivalent experience. * 4+ years of Solutions Engineering (or similar Sales Engineering roles) experience. * Established 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, data center deployments, etc. * Effective time management and capable of balancing multiple tasks. * Ability to communicate ideas clearly through documents, presentation, etc. Ways to stand out from the crowd: * AWS, GCP, Azure or OCI Professional Solution Architect Certifications * Hands-on experience with NVIDIA GPUs and SDKs (i.e. CUDA, Triton, TensorRT-LLM, etc.) * Deep understanding of the full software development lifecycle, including best practices for system design, architectural patterns, and comprehensive testing. * Solid working knowledge of Python * System-level experience, specifically GPU-based systems We make extensive use of conferencing tools, but occasional travel is required for local on-site visits to customers and industry events. We are open to remote work locations! ## Description * Working with Cloud Service Providers to develop and demonstrate solutions based on NVIDIA's groundbreaking software and hardware technologies. * Build and deploy solutions at scale using NVIDIA's AI software on cloud-based GPU platforms. * Build custom PoCs for solutions that address customer's critical business needs while applying NVIDIA's hardware and software technologies. * Partner with Sales Account Managers or Developer Relations Managers to identify and secure business opportunities for NVIDIA products and solutions. * Conduct regular technical customer meetings for project/product details, feature discussions, intro to new technologies, and debugging sessions. * Prepare and deliver technical content to customers including presentations about purpose-built solutions, workshops about NVIDIA products and solutions, etc. ## Related Videos - [Tour de Force: Open-Source LLM Inference Optimization from Simple to Sophisticated](https://www.wearedevelopers.com/videos/100099-tour-de-force-open-source-llm-inference-optimization-from-simple-to-sophisticated) - [From DevOps to Scaled DevOps: How We’re Rebuilding Continuous Delivery as a Platform](https://www.wearedevelopers.com/videos/100018-from-devops-to-scaled-devops-how-we-re-rebuilding-continuous-delivery-as-a-platform) - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [LLMOps-driven fine-tuning, evaluation, and inference with NVIDIA NIM & NeMo Microservices](https://www.wearedevelopers.com/videos/1582-llmops-driven-fine-tuning-evaluation-and-inference-with-nvidia-nim-nemo-microservices) - [Efficient deployment and inference of GPU-accelerated LLMs​](https://www.wearedevelopers.com/videos/929-efficient-deployment-and-inference-of-gpu-accelerated-llms) - [Trends, Challenges and Best Practices for AI at the Edge](https://www.wearedevelopers.com/videos/630-trends-challenges-and-best-practices-for-ai-at-the-edge) ## Related Articles - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [Best US AI Conferences for CTOs in 2026: Build vs. Buy, Vendor Evaluation, and Peer Intelligence](https://www.wearedevelopers.com/magazine/736-best-us-ai-conferences-for-ctos-in-2026-build-vs-buy-vendor-evaluation-and-peer-intelligence) - [Got AI ideas but no money? Here are 10 free ways to level up your AI skills with Google Cloud](https://www.wearedevelopers.com/magazine/600-got-ai-ideas-but-no-money-here-are-10-free-ways-to-level-up-your-ai-skills-with-google-cloud) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [7 Cloud Computing Trends Coming in 2025 for Developers](https://www.wearedevelopers.com/magazine/412-7-cloud-computing-trends-coming-in-2025-for-developers)