Senior Solutions Architect – Safety and Security

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

📋 Description

• Lead strategic engagements for agentic AI partnerships, overseeing processes from discovery and architecture to proof of concept, production readiness, deployment, and scaling.

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

• Collaborate with security independent software vendors (ISVs) to incorporate NVIDIA models into detection and response solutions, including threat triage, investigative agents, remediation workflows, natural language query translation, analyst automation, personally identifiable information (PII) management, and content safety measures.

• Design secure and confidential AI deployment strategies utilizing NVIDIA Confidential Computing, GPU attestation, key management system (KMS) integration, protected infrastructure, air-gapped configurations, and partner key-management workflows.

• Produce proof of concepts, benchmarks, reference architectures, reusable blueprints, field guidance, and product insights to transition secure AI systems into operational environments.

• Enhance the factory planning function.

⛳️ Requirements

• Bachelor's, Master's, or PhD degree in Computer Science, Electrical Engineering, AI/ML, or a related field.

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

• Proven experience in leading projects in AI, ML, distributed systems, or enterprise software from prototype through to production.

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

• Extensive knowledge in 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 prompt injection, jailbreaks, tool-based data exfiltration, unsafe tool invocation, and risks associated with model or skill supply chains.

• Experience with NVIDIA AI software, including NIM, NeMo Framework, NeMo Retriever, NeMo Guardrails, NeMo Agent Toolkit, Dynamo, Nemotron, Triton, TensorRT-LLM, or NIM Operator.

• Background in LLM red-teaming, AI safety evaluation, 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 constructing post-training pipelines or GPU-accelerated safety and security processes.

• Familiarity with 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.