Lead Enterprise AI Architect, Enterprise AI Platform - Agentic AI at NVIDIA

Santa Clara, California, United States

Apply Now

Not SpecifiedCompensation

Expert & Leadership (9+ years)Experience Level

Full TimeJob Type

UnknownVisa

Artificial Intelligence, TechnologyIndustries

Requirements

Bachelor’s degree in Computer Science or related field (or equivalent experience); Master’s or PhD preferred
15+ years of demonstrable experience in software architecture, systems design, or enterprise platform engineering
Deep expertise in architecting large-scale distributed systems with a focus on reliability, performance, and security
Demonstrated proficiency in AI/ML systems, generative AI, or agentic AI frameworks
Familiarity with large language models, RAG pipelines, orchestration frameworks (e.g., ReAct, LangChain, AutoGPT-like flows)
Experience integrating enterprise platforms (e.g., ERP, CRM, ITSM) with APIs, data connectors, or custom services
Hands-on development of AI agents, frameworks, and tooling, including setting architectural and coding standards
Solid understanding of security, governance, and compliance for AI in enterprise contexts
Excellent collaboration skills with the ability to influence cross-functional stakeholders and build trusted partnerships
Ability to communicate complex architectural concepts clearly and inspire confidence across technical and business audiences
Ways to stand out
Hands-on experience with containerized deployments, Kubernetes, and hybrid cloud/on-prem environments
Prototyping skills in Python with ability to build proof-of-concept agent workflows
Experience with NVIDIA AI technologies such as NeMo, NeMo Guardrails, AIQ, or GPU-optimized inference stacks
Track record of publishing technical papers, architecture patterns, or thought leadership in AI systems
Knowledge of observability tools, telemetry dashboards, and evaluation frameworks for AI agent performance as well as experience solving real-world problems with AI in IT, supply chain, or finance domains

Responsibilities

Define and evolve the architecture for NVIDIA’s Enterprise AI Platform, including frameworks for agent orchestration, multi-agent coordination, RAG, deployment, monitoring, and life cycle management
Architect and enable data flywheels that drive continuous improvement of AI agents through evaluation, feedback, and iteration loops
Partner with engineering, product, and research teams to shape platform strategy and roadmaps, while evaluating LLMs, agentic frameworks, and NVIDIA’s own NeMo and AIQ technologies
Ensure integration with enterprise data sources and tools (e.g., ServiceNow, Salesforce, SAP, Workday, GDrive, SharePoint, Confluence) with strong content security focus
Drive architectural decisions across deployment models (on-prem, cloud, hybrid, containerized) to deliver scalable, reliable, and efficient solutions
Lead design reviews, develop technical documentation, and mentor engineers in principles of architecture and code development
Champion observability, monitoring, versioning, and telemetry to ensure trustworthy and auditable AI agents
Influence enterprise adoption of the platform by partnering with stakeholders across IT, chip design, supply chain, sales, finance, and HR, and serve as a reference adopter providing feedback to strengthen NVIDIA’s ecosystem

Skills

RAG

LLMs

NeMo

AIQ

ServiceNow

Salesforce

SAP

Workday

GDrive

SharePoint

Confluence

Agent Orchestration

Observability

Telemetry

Containerized Deployment

NVIDIA

Designs GPUs and AI computing solutions

About NVIDIA

NVIDIA designs and manufactures graphics processing units (GPUs) and system on a chip units (SoCs) for various markets, including gaming, professional visualization, data centers, and automotive. Their products include GPUs tailored for gaming and professional use, as well as platforms for artificial intelligence (AI) and high-performance computing (HPC) that cater to developers, data scientists, and IT administrators. NVIDIA generates revenue through the sale of hardware, software solutions, and cloud-based services, such as NVIDIA CloudXR and NGC, which enhance experiences in AI, machine learning, and computer vision. What sets NVIDIA apart from competitors is its strong focus on research and development, allowing it to maintain a leadership position in a competitive market. The company's goal is to drive innovation and provide advanced solutions that meet the needs of a diverse clientele, including gamers, researchers, and enterprises.

Santa Clara, CaliforniaHeadquarters

1993Year Founded

$19.5MTotal Funding

IPOCompany Stage

Automotive & Transportation, Enterprise Software, AI & Machine Learning, GamingIndustries

10,001+Employees

Benefits

Company Equity

401(k) Company Match

Risks

Increased competition from AI startups like xAI could challenge NVIDIA's market position.

Serve Robotics' expansion may divert resources from NVIDIA's core GPU and AI businesses.

Integration of VinBrain may pose challenges and distract from NVIDIA's primary operations.

Differentiation

NVIDIA leads in AI and HPC solutions with cutting-edge GPU technology.

The company excels in diverse markets, including gaming, data centers, and autonomous vehicles.

NVIDIA's cloud services, like CloudXR, offer scalable solutions for AI and machine learning.

Upsides

Acquisition of VinBrain enhances NVIDIA's AI capabilities in the healthcare sector.

Investment in Nebius Group boosts NVIDIA's AI infrastructure and cloud platform offerings.

Serve Robotics' expansion, backed by NVIDIA, highlights growth in autonomous delivery services.

Land your dream remote job 3x faster with AI

Try Jobo Free