Level

NVIDIA

Solution Architect - Agentic AI

NVIDIA is hiring a Solution Architect - Agentic AI for a remote role open to applicants in Germany. Level rates it ; you can apply on Level.

AI in this role

Solution Architect specializing in agentic AI to help partners build enterprise-ready agentic AI products on the NVIDIA stack.

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ragsolution-architectureagentic-aiai-infrastructuresystem-integration

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people.  

Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world. 


Join us at NVIDIA, where we are pushing the boundaries of AI to develop the future of computing! Our Agentic AI Applications and Specialized Agents team is leading this transformation, driving innovation in AI-native software. As a Solutions Architect, you’ll play a pivotal role in helping our partners build enterprise-ready agentic AI products on the NVIDIA stack. This outstanding opportunity allows you to work with innovative technology and collaborate with individuals known for their creativity and problem-solving skills in the industry. You’ll be instrumental in making NVIDIA the technical foundation for AI application wrappers, orchestrating agents, and specialized workflows. 


What You’ll Be Doing:

  • Lead deep technical discovery with AI application wrapper partners to understand their product architecture, agent topology, and orchestration model. 
  • Build reference architectures that integrate NVIDIA NIM, Nemotron, model routing, Dynamo, NeMo, AI-Q, CUDA-X libraries, OpenShell, and NemoClaw. 
  • Build hands-on proofs of concept to demonstrate how partners can evolve from general-purpose AI wrappers to specialized, enterprise-ready agent platforms. 
  • Use DGX Spark for local agent demos, secure sandboxed workflows, developer playbooks, pilot environments, and desktop-scale benchmarking for agentic use cases. 
  • Standardize on NIM plus Dynamo for serving patterns in agentic applications, ensuring fast time to first token and multi-turn reasoning retention. 
  • Help partners integrate secure runtime patterns including sandboxing, policy enforcement, and human-in-the-loop control points. 
  • Support multi-stage deployment paths from local DGX Spark development to on-prem, sovereign, hybrid cloud, or AI Factory infrastructure rollouts. 
  • Optimize end-to-end agentic workloads for latency, throughput, retrieval quality, cost efficiency, and GPU utilization. 
  • Develop reusable enablement assets like reference architectures, workshop content, benchmark reports, and playbooks for agentic application wrappers. 

What We Need To See:

  • BS, MS, PhD or equivalent experience in Computer Science, Electrical/Computer Engineering, Physics, Mathematics, or a related engineering field—or equivalent practical experience.
  • 8+ years in building, deploying, or supporting production LLM or agentic AI systems. 
  • Strong Python programming and practical proficiency with TypeScript or JavaScript. 
  • Practical knowledge of orchestration frameworks, agent frameworks, RAG platforms, workflow automation systems, or AI application builders. 
  • Familiarity with model serving and inference optimization, including NIM and Dynamo. 
  • Experience with Kubernetes, Helm, containers, and GPU-backed workloads in cloud, hybrid, or on-prem environments. 
  • Ability to debug across the full stack: application code, APIs, model endpoints, orchestration layers, retrieval systems, infrastructure, and security controls. 
  • Expertise in working directly with customers in architectural roles and the capability to impact both creators and corporate decision-makers. 
  • Comfort with uncertainty and the ability to rapidly transition from idea to proof of concept. 

Ways To Stand Out From The Crowd:

  • Practical experience working directly with NVIDIA NIM, Nemotron, NeMo, Dynamo, AI-Q, OpenShell, NemoClaw, or NVIDIA AI Enterprise. 
  • Experience with platforms like Lovable, n8n, Haystack, LangChain, LlamaIndex, AutoGen, CrewAI, or MCP-based systems. 
  • Expertise in secure agent runtime build, sandboxing, tool permissioning, confidential computing, policy-as-code, or enterprise governance controls. 
  • Familiarity with DGX Spark as a local AI development platform, or experience crafting developer playbooks bridging desktop prototyping to data-center deployment. 
  • Background in sovereign AI, regulated enterprise environments, or private/on-prem deployment models. 

NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. If you're creative and autonomous, we want to hear from you! 

NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law. 

If you are passionate about NVIDIA technology, we should talk! 

 

How we rate this

Solution Architect - Agentic AI at NVIDIA rates 65 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.

Classification

Works on AI. The daily work is on AI products, without building the model.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.

Prepare for this job

A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.

Skills and AI tools this role asks for

RAGSolution ArchitectureAgentic AIAI InfrastructureSystem IntegrationLangChainLlamaIndexCrewAI

Questions you could be asked

  1. How would you design a retrieval step so the model answers from real data instead of guessing?
  2. Tell me about a project where solution architecture was part of your work. What did you do?
  3. Tell me about a project where agentic ai was part of your work. What did you do?
  4. Tell me about a project where ai infrastructure was part of your work. What did you do?
  5. Tell me about a project where system integration was part of your work. What did you do?

Adapt your resume

  • List these exact terms on your resume: RAG, Solution Architecture, Agentic AI, AI Infrastructure, and System Integration. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
  • Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.

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