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This listing doesn't post a salary. Most similar roles pay
$160,000–$235,750.
Based on 240 similar postings.
Employer
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
on FindRole.
Listed pay typically runs
$184,000–$287,500
across 1110 roles with salary data.
The Senior Solutions Architect, Agentic AI — Safety and Security joins the team to help enterprise ISVs design, build, and deploy secure agentic AI systems on accelerated computing platforms. You will lead strategic partner engagements from discovery through production, building enterprise-grade systems featuring multi-agent workflows, RAG, tool use, and policy enforcement. Responsibilities include architecting secure deployments using confidential computing, GPU attestation, and KMS integration while creating reference architectures and benchmarks. You must possess expertise in LLM security, distributed systems, and production-level generative AI. Required skills include Python, Linux, PyTorch, and TensorFlow. You will address technical challenges such as prompt injection, jailbreaks, and data exfiltration while integrating models into cybersecurity products for threat triage, analyst automation, and content safety within protected infrastructure environments.
What does a Solutions Architect earn in California?
Median $235750 from 57 postings across 11 companies.
Lead strategic agentic AI partner engagements from initial discovery through production rollout and scaling.
Build enterprise-grade agentic AI systems featuring multi-agent workflows, RAG, planning, and guardrails.
Integrate NVIDIA models into cybersecurity products for threat triage, remediation workflows, and analyst automation.
Architect secure AI deployments using confidential computing, GPU attestation, and air-gapped infrastructure patterns.
Create PoCs, benchmarks, and reusable blueprints to move secure AI systems into production.
Implement policy enforcement, failure containment, and PII handling within agentic AI frameworks.
Provide technical guidance and product feedback to help partners deploy trustworthy AI products.
What we're looking for
BS, MS, or PhD in Computer Science, Electrical Engineering, AI/ML, or equivalent experience.
8+ years in engineering, solutions architecture, applied ML, enterprise software, or technical deployment.
Experience leading AI, ML, distributed systems, or enterprise software projects from prototype to production.
Hands-on experience building LLM, generative AI, RAG, or agentic AI applications in production or production-like environments.
Depth in AI/LLM security, enterprise cybersecurity, trust and safety, confidential computing, secure AI infrastructure, model customization, post-training, or model evaluation.
Strong Python and Linux skills with experience in PyTorch, TensorFlow, or similar frameworks.
Experience with NVIDIA AI software such as NIM, NeMo Framework, NeMo Retriever, NeMo Guardrails, NeMo Agent Toolkit, Dynamo, Nemotron, Triton, or TensorRT-LLM (preferred).
Experience with LLM red-teaming, AI safety evaluation, adversarial testing, or secure tool invocation (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