Senior Solutions Architect – Agentic AI, Safety and Security

This is a fully remote position, open to applicants in California, +1 more state.

📋 Description

• Oversee strategic partnerships for agentic AI, guiding them from discovery and architecture through proof of concept, production readiness, deployment, and scaling.

• Develop enterprise-level agentic AI systems that incorporate multi-agent workflows, tool-utilizing agents, retrieval-augmented generation (RAG), planning, memory, evaluation, guardrails, policy enforcement, and failure mitigation.

• Collaborate with security independent software vendors (ISVs) to integrate NVIDIA models into detection and response tools.

• Assist with threat triage, investigation agents, remediation workflows, natural language query conversion, analyst automation, personally identifiable information (PII) handling, and content safety measures.

• Design secure and confidential AI implementations using NVIDIA Confidential Computing, GPU attestation, key management system (KMS) integration, protected infrastructure, air-gapped designs, and partner key-management processes.

• Generate proof of concepts, benchmarks, reference architectures, reusable templates, field guidance, and product feedback.

• Facilitate the transition of secure AI systems into production for NVIDIA and its partners.

⛳️ Requirements

• Bachelor’s, Master’s, or PhD in Computer Science, Electrical Engineering, AI/ML, or equivalent experience.

• Over 8 years of experience in engineering, solutions architecture, applied machine learning, enterprise software, or technical deployment.

• Proven experience leading AI, ML, distributed systems, or enterprise software projects from the prototype stage to full production.

• Practical experience in developing large language models (LLM), generative AI, retrieval-augmented generation (RAG), or agentic AI applications in production or similar environments.

• Expertise in one or more areas including AI/LLM security, enterprise cybersecurity, trust and safety, confidential computing, secure AI infrastructure, model customization, post-training processes, or model evaluation.

• Proficient in Python and Linux.

• Familiarity with frameworks such as PyTorch, TensorFlow, or similar technologies.

• Understanding of risks related to prompt injection, jailbreaks, tool-based data exfiltration, unsafe tool invocation, and model or skill supply-chain vulnerabilities.

• 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.

• Background in LLM red-teaming, AI safety evaluations, adversarial testing, prompt-injection defense, policy enforcement, Garak, NeMo Auditor, or release-gating evaluation benchmarks.

• Knowledge of 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 in building post-training pipelines or GPU-accelerated safety and security workflows.

• Familiarity with confidential computing technologies, including GPU confidential computing, remote attestation, Confidential Containers, enterprise KMS, air-gapped deployments, AMD SEV-SNP, or Intel TDX.

🏝️ Benefits

• Competitive salaries.

• Comprehensive benefits package.

• Equity opportunities.

• Additional benefits.