NVIDIA

Senior Solutions Architect, Agentic AI — Safety and Security

Santa Clara, CA, US$184,000-$287,500Posted 10 days ago

Job Description

We are looking for a Senior Solutions Architect to help leading Enterprise ISVs design, build, and deploy secure agentic AI systems on NVIDIA’s accelerated computing platform.

In this role, we will partner with strategic software companies across cybersecurity, AI safety, infrastructure protection, and confidential computing. Together, we will help them build trustworthy AI products that meet enterprise expectations for security, privacy, safety, reliability, and performance.

This work includes multi-agent orchestration, guardrails, agent runtime security, RAG, tool use, model customization, policy enforcement, OpenShell-like execution environments, and confidential AI deployments on protected infrastructure.

What you'll be doing

  • Lead strategic agentic AI partner engagements from discovery and architecture through PoC, production readiness, rollout, and scale.
  • Build enterprise-grade agentic AI systems with multi-agent workflows, tool-using agents, RAG, planning, memory, evaluation, guardrails, policy enforcement, and failure containment.
  • Partner with security ISVs to integrate NVIDIA models into detection and response products, including threat triage, investigation agents, remediation workflows, natural-language-to-query, analyst automation, PII handling, and content safety.
  • Architect secure and confidential AI deployments using NVIDIA Confidential Computing, GPU attestation, KMS integration, protected infrastructure, air-gapped patterns, and partner key-management workflows.
  • Create PoCs, benchmarks, reference architectures, reusable blueprints, field guidance, and product feedback that help NVIDIA and our partners move secure AI systems into production.

What we need to see

  • 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 sy

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