Senior Architect, Agentic AI for Marketing

🔥 0 minutes ago

🏄 California – Remote

🏄 California – Remote

💵 $224k - $356.5k / year

⏰ Full Time

🟠 Senior

🤖 Artificial Intelligence

🦅 H1B Visa Sponsor

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👻 Ghost score 1%

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NVIDIA

WebsiteLinkedInAll Job Openings

10,000+ employees

Founded 1993

🏥 Healthcare

🏭 Manufacturing

🤖 Artificial Intelligence

Healthcare • Manufacturing • Artificial Intelligence

NVIDIA is a leading technology company specializing in accelerated computing and artificial intelligence. NVIDIA pioneers advancements in graphical processing units (GPUs), cloud computing, data centers, and virtual reality, with a focus on gaming, automotive, healthcare, and robotics industries. The company's innovations, such as NVIDIA Omniverse, transform traditional digital processes by enabling high-fidelity simulations and rendering tasks. Their applications span various industries, from autonomous vehicles using NVIDIA DRIVE to healthcare solutions with NVIDIA Clara, and AI-driven analytics and workflows.

📋 Description

• Lead the architecture and delivery of Agentic AI solutions supporting NVIDIA Marketing, including personalization, content discovery, campaign intelligence, recommendations, internal copilots, workflow automation, and customer-facing AI experiences • Translate business and marketing needs into practical agent architectures covering goals, tools, retrieval, memory, planning, human-in-the-loop workflows, evaluation criteria, and production operating models • Advance NVIDIA Marketing’s agentic AI platform through agent-tool gateways, multi-agent orchestration, conversational data assistants, recommendation APIs, embedding pipelines, contextual retrieval, model adapters, catalog intelligence, and production AI infrastructure • Shape the platform roadmap for agent registries, tool catalogs, permission models, memory and state services, evaluation frameworks, observability, reusable agent patterns, and lifecycle management • Partner with engineers to design reliable interfaces for agent invocation, tool execution, response formats, memory, state management, and integrations with marketing platforms, analytics systems, chat experiences, and content repositories • Establish production practices for evaluation, regression testing, observability, latency, cost, reliability, safety, access controls, auditability, fallback behavior, and incident response • Guide technical tradeoffs across model quality, retrieval precision, inference cost, throughput, latency, personalization, data freshness, privacy, security, and business impact • Build prototypes, reference architectures, technical blueprints, and reusable components for scalable production systems

🎯 Requirements

• BS, MS, or PhD in Computer Science, AI/ML, Electrical Engineering, Data Science, a related technical field, or equivalent experience • 12+ years of experience in software engineering, AI/ML engineering, solutions architecture, applied AI, data platforms, or large-scale production systems • Experience building and deploying applications involving LLMs, generative AI, RAG, recommendation systems, conversational AI, or agentic AI • Strong programming skills in Python • Experience with APIs, Linux environments, distributed systems, containers, cloud-native infrastructure, and production debugging • Understanding of agentic AI system design, including tool use, orchestration, planning, memory, retrieval, evaluation, guardrails, human approval, and failure handling • Experience designing integrations between AI agents and enterprise tools using MCP, function calling, API gateways, or related interoperability patterns • Experience developing conversational AI experiences grounded in structured or semi-structured data • Experience with production AI or software infrastructure, including model serving, Kubernetes, Docker, CI/CD, observability, monitoring, health checks, performance testing, or cost optimization • Demonstrated ownership of technical solutions across architecture, development, deployment, integration, and ongoing operations • Ability to navigate ambiguous business problems, translate them into technical approaches, and communicate with technical and non-technical audiences

🏖️ Benefits

• Equity • Benefits