We are seeking a Generative AI Specialist to join our Advanced Technology Partner (ATP) team as a Senior Solutions Architect who thrives at the intersection of deep technical work and real-world enterprise impact. In this role, you will act as a trusted technical advisor and hands-on creator for NVIDIA's most sophisticated AI partners. You will lead groundbreaking prototyping and proof-of-concept collaborations that connect partners with key customers to accelerate the transition from concept to production. This outstanding position encourages you to scope, compose, build, and tackle challenges alongside partners to leave behind reusable assets and validated solutions. If you want to develop how the world’s top organizations adopt and deploy AI at scale, we want to meet you!
What you'll be doing:
Function as the chief technical representative for advanced AI partners, handling detailed technical interactions and synchronizing their roadmaps with NVIDIA's platform and emerging technology.
Lead end-to-end prototyping engagements by defining requirements and crafting reference architectures that guide partners from initial concept to production-ready handoffs.
Architect and build enterprise-grade agentic AI systems, RAG pipelines, and multi-modal workflows, ensuring high-performance, GPU-accelerated inference at scale.
Diagnose and resolve intricate system issues and performance bottlenecks across the full AI stack, from initial model selection to large-scale deployment.
Produce reusable technical assets, including implementation guides and benchmarks, that accelerate time-to-value for both partners and their customers.
Collaborate with NVIDIA’s internal engineering, research, and product teams to resolve critical partner issues and speed up shared success.
Champion team guidelines for technical reviews and discovery, while mentoring new members and participating in hiring panels to expand the team’s depth.
Commit to continuous professional growth through formal AI/ML certifications and special projects that elevate your value within the NVIDIA ecosystem.
What we need to see:
8+ years of relevant engineering experience crafting, developing, and deploying AI/ML systems and complex LLM-powered workflows, with a strong software or ML engineering foundation.
Strong proficiency in advanced GenAI and LLM approaches, including proprietary vs. open model selection, retrieval-augmented generation (RAG), prompt engineering, and production inference optimization.
Familiarity with agentic AI standards (LangGraph, LangChain, MCP) and expertise in multimodal AI systems including vision-language models and audio/video workflows.
Hands-on experience with fine-tuning (PEFT, LoRA), synthetic data generation, and implementing automated AI evaluation frameworks to measure quality and safety.
Strong command of GPU-optimized infrastructure (Docker, Kubernetes), microservices, and MLOps pipelines for automated training and distributed inference.
Experience with AI observability (trace logging, latency monitoring) and a solid understanding of responsible AI, including guardrails, data governance, and regulatory considerations (HIPAA, GDPR).
Experience connecting cloud and on-premises deployments, hybrid architectures, and familiarity with Physical AI concepts such as simulation environments and edge inference.
Proven ability to communicate complex technical concepts to diverse audiences and experience in technical engagement roles involving discovery and requirements gathering.
MS or advanced degree in Computer Science, AI, or a related field—or equivalent experience.
Ways to stand out from the crowd:
Proven track record of leading enterprise AI prototyping engagements — prioritizing, architecting, building, and solving POCs and pilots in complex customer or partner environments.
A tangible body of work demonstrating your builder foundation: open-source contributions, publications, patents, recorded talks, technical blogs, or equivalent public artifacts.
Skilled in NVIDIA's AI software suite including NVIDIA AI Enterprise (NVAIE), NIM inference microservices, NeMo, NeMo Curator, Nemotron model family, NVIDIA Blueprints, TensorRT, Triton Inference Server, CUDA libraries, and NVIDIA Agent Intelligence toolkit (NAI/NAT). Knowledge of new NVIDIA frameworks like NemoClaw/OpenShell.
Experience with Physical AI platforms including NVIDIA Omniverse, Isaac Sim, Jetson edge computing, or involvement in production robotics/autonomous systems implementations.
Active participation in the AI community: conference presentations, open-source project leadership, or recognized expertise in a specific GenAI domain.
You will also be eligible for equity and benefits.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.Top Skills
What We Do
NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”
