About the job
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.
Responsibilities
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.
Qualifications
Minimum
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 one or more areas such as 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, experience with PyTorch, TensorFlow, or similar frameworks, and working knowledge of risks such as prompt injection, jailbreaks, tool-based data exfiltration, unsafe tool invocation, and model or skill supply-chain risk
Preferred
Experience with NVIDIA AI software such as NIM, NeMo Framework, NeMo Retriever, NeMo Guardrails, NeMo Agent Toolkit, Dynamo, Nemotron, Nemotron Safety models, Triton, TensorRT-LLM, or NIM Operator
Experience with LLM red-teaming, AI safety evaluation, adversarial testing, prompt-injection defense, policy enforcement, Garak, NeMo Auditor, or release-gating evaluation benchmarks
Experience with OpenShell, agent harnesses, sandboxed execution, secure tool invocation, agent runtime security, AI/software supply-chain security, model or skill signing, provenance, attestation, VEX, or secure model registries
Experience building post-training pipelines or GPU-accelerated safety and security workflows, including reasoning, tool use, domain adaptation, safety alignment, PII/NER detection, content-safety models, TensorRT optimization, quantization, workshops, architecture reviews, whitepapers, or reference architectures
Experience with confidential computing, including GPU confidential computing, remote attestation, Confidential Containers, enterprise KMS, air-gapped deployments, AMD SEV-SNP, or Intel TDX