Senior Solutions Architect – Agentic AI, Safety and Security

NVIDIA

. Lead strategic agentic AI partner engagements from discovery and architecture through PoC, production readiness, rollout, and scale .

Posted 10/2/2026full-timeRemote • United StatesSenior💰 $184,000 - $287,500 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in leading the development and deployment of secure agentic AI systems, with a strong focus on AI/ML security, confidential computing, and enterprise software architecture. Proficient in building production-ready AI applications using advanced frameworks and methodologies.

Highest-signal resume keywords

AI/ML SecurityPython ProgrammingNVIDIA Confidential ComputingLLM Application DevelopmentEnterprise Software Architecture

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

AI/MLDistributed SystemsGenerative AILLMModel EvaluationPost-TrainingSecure AI InfrastructurePolicy EnforcementTool-Using AgentsFailure Containment

Tools & Technologies

PyTorchTensorFlowNVIDIA AI SoftwareLinuxKMS IntegrationAdversarial TestingPrompt Injection DefenseModel CustomizationField GuidanceReference Architectures

Certifications & Qualifications

BS in Computer ScienceMS in Computer SciencePhD in Computer ScienceEquivalent Experience

Industry Keywords

Agentic AIMulti-Agent WorkflowsConfidential ComputingCybersecurityTrust and SafetySecure Agent ExecutionProduction ReadinessPrototype to ProductionDetection and Response ProductsAir-Gapped Patterns

Tech Stack

Tools & technologies

Cyber SecurityDistributed SystemsLinuxPythonPyTorchTensorflow

About the role

Key responsibilities & impact

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
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 to move secure AI systems into production
Improve NVIDIA’s factory planning function

Requirements

What you’ll need

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
Experience with PyTorch, TensorFlow, or similar frameworks
Working knowledge of prompt injection, jailbreaks, tool-based data exfiltration, unsafe tool invocation, and model or skill supply-chain risk
Experience with NVIDIA AI software, LLM red-teaming, AI safety evaluation, adversarial testing, prompt-injection defense, policy enforcement, secure agent execution, confidential computing, or related technologies is advantageous

Benefits

Comp & perks

Competitive salaries
Generous benefits package
Equity