NVIDIA गेमिंग, डेटा सेंटर, क्लाउड कंप्यूटिंग, स्वास्थ्य सेवा, विनिर्माण, ऑटोमोटिव और रोबोटिक्स सहित विभिन्न क्षेत्रों में उपयोग की जाने वाली त्वरित कंप्यूटिंग और कृत्रिम बुद्धिमत्ता प्रौद्योगिकियाँ विकसित करती है। इसका कार्य ग्राफ़िक्स प्रोसेसिंग यूनिट, AI प्लेटफ़ॉर्म, सिमुलेशन और उद्योग-केंद्रित समाधानों तक फैला हुआ है। इनमें सहयोगात्मक 3D वर्कफ़्लो के लिए NVIDIA Omniverse, स्वायत्त वाहन विकास के लिए NVIDIA DRIVE और स्वास्थ्य सेवा अनुप्रयोगों के लिए NVIDIA Clara शामिल हैं। कंपनी उन्नत कंप्यूटिंग, सिमुलेशन और AI-आधारित विश्लेषणों को समर्थन देने वाले बुनियादी ढाँचे और सॉफ़्टवेयर पर काम करने वाली बड़ी तकनीकी टीमों को एक साथ लाती है।
Senior Solutions Architect, Agentic AI Safety and Security — NVIDIA (Remote)
Lead secure agentic AI initiatives for NVIDIA’s enterprise software partners, from initial architecture through production deployment. The role covers confidential computing, security controls, partner integrations, and scalable AI system design.
संयुक्त राज्य
कैलिफ़ोर्निया
टेक्सास$1,84,000 – $2,87,500 / वर्ष
रिमोटपूर्णकालिकवरिष्ठआवश्यक भाषा: अंग्रेज़ीसमाधान इंजीनियरविवरण
- Guide strategic agentic AI partner engagements from discovery and architecture through proof of concept, production readiness, rollout, and scale
- Design enterprise agentic AI systems using multi-agent workflows, tool-enabled agents, RAG, planning, memory, evaluation, guardrails, policy enforcement, and failure containment
- Work with security ISVs to embed NVIDIA models into detection and response products
- Design secure, confidential AI deployments involving NVIDIA Confidential Computing, GPU attestation, KMS integration, protected infrastructure, air-gapped architectures, and partner key-management processes
- Develop proofs of concept, benchmarks, reference architectures, reusable blueprints, field guidance, and product feedback that help secure AI systems reach production
- Support improvements to NVIDIA’s factory planning function
आवश्यकताएँ
- Bachelor’s, master’s, or doctoral degree in Computer Science, Electrical Engineering, AI/ML, or equivalent professional experience
- At least 8 years of experience in engineering, solutions architecture, applied machine learning, enterprise software, or technical deployment
- Track record of taking AI, machine learning, distributed systems, or enterprise software projects from prototype to production
- Practical experience developing LLM, generative AI, RAG, or agentic AI applications for production or production-like environments
- Expertise in AI and LLM security, enterprise cybersecurity, trust and safety, confidential computing, secure AI infrastructure, model customization, post-training, or model evaluation
- Advanced proficiency with Python and Linux
- Experience using PyTorch, TensorFlow, or comparable machine learning frameworks
- Working knowledge of prompt injection, jailbreaks, tool-based data exfiltration, unsafe tool invocation, and model or skill supply-chain threats
- Experience with NVIDIA AI software, LLM red teaming, AI safety evaluation, adversarial testing, prompt-injection defenses, policy enforcement, secure agent execution, confidential computing, or related technologies is beneficial
लाभ
- Competitive compensation
- Comprehensive benefits package
- Equity participation