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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Solutions Architect, Inference Deployments - **Company:** NVIDIA Ltd. - **Location:** Santa Clara, CA, United States - **Experience:** Expert - **Salary:** $152,000.0 - $241,500.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Artificial Neural Networks, Program Optimization, DevOps, Distributed Systems, Dynamic Random-Access Memory, Open Source Technology, Remote Direct Memory Access, Large Language Models, Kubernetes, TensorRT, Nim (Programming Language), Decoding - **Published:** May 30, 2026 - **Apply:** https://www.juju.com/job/00000000g3ivu8 ## About the Role + 5+ Years in Solutions Architecture with a proven track record of deploying distributed systems and AI inference workloads on Kubernetes. + Experience with one of NVIDIA Dynamo, Triton Inference Server, or TensorRT-LLM for model optimization and serving. + GPU orchestration using NVIDIA GPU Operator, NIM Operator, and Multi-Instance GPU (MIG) partitioning. + Solving sophisticated GPU allocation, memory hierarchies (HBM, DRAM, SSD), and low-latency networking (RDMA, UCX). + Demonstrated success in tuning large language models for low-latency inference in enterprise environments. + BS in CS/Engineering or equivalent experience. Ways to stand out from the crowd: + Prior experience deploying NVIDIA inference technologies such as Dynamo, NIM, NIXL and Grove. + Deep understanding of transformer neural network, and inference acceleration technologies like quantization, speculative decoding, WideEP etc. + NVIDIA Certified AI Engineer or similar credentials. + Contributions to open-source projects including NVIDIA Dynamo, vLLM, KServe, or SGLang. ## Description We're forming a team of innovators to roll out and enhance AI inference solutions at scale, demonstrating NVIDIA's GPU technology and Kubernetes. As a Solutions Architect focused on inference, you'll collaborate closely with our engineering, DevOps, and customers to develop enterprise AI solutions. Together, we'll deliver generative AI to production! What you'll be doing: + Build inference pipelines with tools like NVIDIA Dynamo, distributing tasks among GPU workers to improve efficiency. + Collaborate with DevOps teams to orchestrate disaggregated inference using Kubernetes for complex workloads. + Accelerate inference pipelines using TensorRT-LLM, vLLM, SGLang, and other backends to ensure seamless integration with disaggregated inference. + Provide mentorship and technical leadership to customers and internal teams, guiding them through the deployment of disaggregated inference systems and resolving complex issues. ## 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) - [Your Next AI Needs 10,000 GPUs. Now What?](https://www.wearedevelopers.com/videos/1590-your-next-ai-needs-10-000-gpus-now-what) - [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) - [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) - [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) ## Related Articles - [Stephan Gillich - Bringing AI Everywhere](https://www.wearedevelopers.com/magazine/489-stephan-gillich-bringing-ai-everywhere) - [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) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering) - [Got AI ideas but no money? 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