Agentic AI Solutions Architect

NVIDIA

Schweiz

On-site

CHF 150,000 - 210,000

Full time

2 days ago
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Job summary

NVIDIA is seeking an experienced Solutions Architect to guide the design and deployment of enterprise‑grade agentic AI solutions built on the NVIDIA stack. You will lead technical discovery, craft reference architectures, and develop proofs of concept with partners to advance from generic AI wrappers to specialized, production‑ready agent platforms.

You will collaborate with customers to shape architectures, ensure secure and scalable deployments, and optimize performance across local, hybrid,

Qualifications

  • 8+ years building, deploying, or supporting production LLM or agentic AI systems.
  • Strong Python programming and practical proficiency with TypeScript or JavaScript.
  • Familiarity with model serving and inference optimization, including NIM and Dynamo.
  • Experience with Kubernetes, Helm, containers, and GPU-backed workloads.

Responsibilities

  • Lead deep technical discovery with AI application wrapper partners to understand product architecture and orchestration models.
  • Build reference architectures that integrate NVIDIA tools and libraries for agentic platforms.
  • Develop hands-on proofs of concept to demonstrate evolution from wrappers to enterprise-ready agent platforms.
  • Optimize end-to-end agentic workloads for latency, throughput, and GPU utilization.

Skills

Python
TypeScript
Kubernetes
Architectural leadership
Customer-facing
Problem solving

Education

BS/MS/PhD

Tools

NIM
Dynamo
NeMo
NVIDIA stack

Job description

NVIDIA is seeking an experienced Solutions Architect to guide the design and deployment of enterprise‑grade agentic AI solutions built on the NVIDIA stack. You will lead technical discovery, craft reference architectures, and develop proofs of concept with partners to advance from generic AI wrappers to specialized, production‑ready agent platforms.

You will collaborate with customers to shape architectures, ensure secure and scalable deployments, and optimize performance across local, hybrid,

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