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$160,937–$235,750.
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About Nvidia
Nvidia is a leading designer of graphics processing units (GPUs) and system-on-chip units, powering gaming, professional visualization, data centers, and artificial intelligence workloads. Industry: Semiconductors & AI Computing
Nvidia currently has
1623 open roles
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Listed pay typically runs
$184,000–$287,500
across 1110 roles with salary data.
Senior Solutions Architect, Agentic AI joins the Solutions Architect team to develop, build, and deploy agentic AI systems for Media & Entertainment companies. This hands-on role involves architecting and writing code to transform large language model capabilities into autonomous agents for content creation, localization, and metadata enrichment. You will build multi-agent systems, retrieval pipelines, and optimized inference stacks using Python, C/C++, PyTorch, and orchestration frameworks like LangGraph, LlamaIndex, CrewAI, and LangChain. Key responsibilities include optimizing inference performance on the NVIDIA AI stack, including NIM, NeMo, and TensorRT-LLM, while deploying workloads on public clouds or on-premise. You will solve production challenges by creating high-performance RAG pipelines over heterogeneous media assets and building reusable blueprints for complex media supply chain operations.
What does a Solutions Architect earn in California?
Median $235750 from 57 postings across 11 companies.
Architect, build, and ship end-to-end Agentic AI applications for Media & Entertainment use cases.
Develop multi-agent systems, retrieval pipelines, and optimized inference stacks on NVIDIA’s accelerated computing platform.
Build high-performance RAG pipelines over heterogeneous media assets including text, images, audio, and video.
Act as a hands-on technical advisor to build, prototype, and deploy Agentic solutions for customers.
Optimize inference performance and total cost of ownership using the full NVIDIA AI inference stack.
Create proofs-of-concept, reference architectures, and reusable blueprints to serve as production templates.
Translate customer feedback into actionable product insights and roadmap requirements for internal engineering teams.
Scale global expertise through the creation of technical collateral, workshops, and developer community engagement.
What we're looking for
BS/MS/PhD in Computer Science, Electrical/Computer Engineering, Physics, Mathematics, AI/ML, or a related field (or equivalent experience).
8+ years as an ML/Software Engineer or Solutions Architect writing production-level code in Python and/or C/C++ in Linux environments.
Validated experience building sophisticated agentic and multi-agent AI systems using frameworks like LangGraph, LlamaIndex, CrewAI, LangChain, or OpenAI Agents SDK.
Strong background in PyTorch and distributed GPU (post-)training to build scalable GPU-accelerated architectures.
Experience deploying workloads at scale on public cloud (AWS, GCP, Azure, OCI) or on-premise.
Strong grasp of the M&E industry paired with excellent communication and presentation skills.
Practical experience working directly with the NVIDIA agentic AI software stack (preferred).
Expertise building LLM evaluation harnesses, benchmarking systems, and optimizing reasoning-focused LLMs and SLMs (preferred).
Agentic AI
LLMs
Generative AI
RAG
Python
Kubernetes
Docker
CI/CD
LangChain
LlamaIndex
LangGraph
NVIDIA NeMo
Triton
API Gateways
Distributed Systems
Model Serving
Observability
Text-to-SQL
Linux
Azure AI Foundry
Copilot Studio
Power Platform
Python
RAG
LangGraph
Microsoft Agent Framework
Power Automate
Dataverse
Azure OpenAI SDK
Azure AI Search
Container Apps
Azure CLI
GitHub Copilot
Claude Code
Agent 365