Senior Architect, Agentic AI for Marketing

Details

NVIDIA is looking for a Senior Architect to help shape the next generation of Agentic AI platforms for NVIDIA Marketing. The role combines technical leadership with hands-on engineering to translate marketing opportunities—including personalization, customer journeys, content intelligence, recommendations, campaign operations, and field enablement—into reliable AI agents and reusable platform capabilities.

The team works at the intersection of applied AI, agentic systems, marketing technology, enterprise data, and production platforms. The role involves leading complex initiatives from discovery through architecture, prototyping, evaluation, deployment, observability, governance, and scale.

Responsibilities

• Lead the architecture and delivery of Agentic AI solutions supporting personalization, content discovery, campaign intelligence, recommendations, internal copilots, workflow automation, and customer-facing AI experiences.
• Translate business and marketing needs into practical agent architectures involving goals, tools, retrieval, memory, planning, human-in-the-loop workflows, evaluation criteria, and production operating models.
• Advance NVIDIA Marketing's agentic AI platform using capabilities such as 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 across 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 agentic systems, including evaluation, regression testing, observability, latency, cost, reliability, safety, access controls, auditability, fallback behavior, and incident response.
• Guide technical trade-offs involving 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 to move promising ideas into 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, retrieval-augmented generation (RAG), recommendation systems, conversational AI, or agentic AI.
• Strong programming skills in Python, with experience working 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 integrating AI agents with enterprise tools using MCP, function calling, API gateways, or related interoperability patterns.
• Experience developing conversational AI experiences grounded in structured or semi-structured data, including text-to-SQL, intent classification, multi-turn dialogue, retrieval, or connections to live data sources.
• Experience with production AI or software infrastructure, such as 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 effectively with technical and non-technical audiences.

Preferred Qualifications

• Experience with production multi-agent systems, agent runtimes, agent frameworks, or tool-using agents.
• Experience with NVIDIA NeMo Agent Toolkit, LangGraph, LlamaIndex, LangChain, CrewAI, Semantic Kernel, OpenAI Agents SDK, Google ADK, or similar technologies.
• Experience with NVIDIA AI software, including NIM, NeMo, NeMo Retriever, NeMo Guardrails, NeMo Agent Toolkit, Nemotron, Triton, NVIDIA AI Enterprise, or GPU-enabled Kubernetes environments.
• Experience with MCP or agent-tool interoperability, including authenticated tool routing, server registries, enterprise tool catalogs, or policy-aware agent gateways.
• Experience with agent evaluation and observability, including traces, tool-call monitoring, offline and online evaluations, regression testing, quality dashboards, or business outcome measurement.

Compensation and Benefits

The base salary range is $224,000–$356,500 USD, determined by location, experience, and the pay of employees in similar positions. The role is also eligible for equity and benefits.

Applications will be accepted at least until August 28, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes and is an equal opportunity employer.