Senior Product Integration Lead, Partner Platforms and GenAI at NVIDIA

Santa Clara, California, United States

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Not SpecifiedCompensation

Senior (5 to 8 years), Expert & Leadership (9+ years)Experience Level

Full TimeJob Type

UnknownVisa

Technology, Artificial IntelligenceIndustries

Requirements

8+ years of proven experience in technical Product or Engineering roles in Enterprise Software, Cloud Platforms, and production deployments with a focus on building partner integrations
Masters or PhD in Computer Science, Electrical Engineering or equivalent experience
Strong background in AI/ML and Deep Learning with hands-on experience building enterprise-grade GenAI systems such as intricate RAGs, Multi-Agent architectures, and production LLM deployments
Experience with programming languages and libraries such as HuggingFace, LangChain, Python, PyTorch, NVIDIA NeMo, vLLM, AutoGen, TensorRT-LLM, etc. and LLM application stages such as Pre-training, Customization, Inference, Evaluation, and Benchmarking
Ability to swiftly research, prototype, and collaborate with multiple teams to arrive at the best technical solution for new and evolving GenAI customer scenarios driving to completion, demonstrating teamwork and ownership

Responsibilities

Build and drive the technical integration of our GenAI offerings across a focused set of ISV and CSP Platforms, collaborating closely with their Platform Architects
Define technical objectives, timelines, and product adoption strategy, aligning with each partner’s long-term business objectives
Hands-on design and ship methodologies, code, and reference architectures that bring RAG, LLM inference, and Multi-Agent workflows to life using NVIDIA libraries (NeMo, NIMs, Triton, Tensor-RT, etc.) as well as vLLM, LangChain, vector DBs, MCP, A2A, and related technologies, deployed across major CSP platforms such as AWS, Azure, GCP, etc
Own the technical product engagement. Drive regular meetings, progress tracking, adoption status, and internal reporting consistent with NVIDIA's culture. Work closely with NVIDIA Product, Engineering, Research, Solution Architecture, and other organizations to achieve the most efficient solution
Develop understanding across all stages of GenAI lifecycle with depth in select areas such as Data Curation, LLM Pre-training, Finetuning such as PEFT, SFT, post-training, Reasoning, RAG, Multi-agent workflows and LLM Inference for production deployments
Represent Partner needs and architecture design to Product and Engineering teams. Contribute to Product roadmap by articulating insights from large-scale enterprise environments and cross-industry patterns, captured from ISV engagements
Develop expertise in GenAI Platform Architecture and keep up to date with the latest in the industry and NVIDIA libraries, models, and frameworks to best support the partner Platform teams

Skills

Key technologies and capabilities for this role

Generative AILLMNeMoNIMTritonTensorRTvLLMLangChainRAGMulti-Agent workflowsvector DBsAI/ML

Questions & Answers

Common questions about this position

What is the employment type for this role?

This is a full-time position.

Is this role remote or does it require office presence?

This information is not specified in the job description.

What technical skills are required for this position?

The role requires hands-on experience with NVIDIA libraries like NeMo, NIMs, Triton, Tensor-RT, as well as vLLM, LangChain, vector DBs, and deployment across AWS, Azure, GCP. Deep knowledge of the GenAI lifecycle including RAG, LLM inference, multi-agent workflows, data curation, finetuning (PEFT, SFT), and production deployments is essential.

What is the company culture like at NVIDIA for this role?

The role involves driving regular meetings, progress tracking, adoption status, and internal reporting consistent with NVIDIA's culture, while working closely with Product, Engineering, Research, Solution Architecture, and other teams.

What makes a strong candidate for this Senior Product Integration Lead role?

A strong candidate combines deep AI/ML applications knowledge with a systems mindset, hands-on technical execution skills, and the ability to build trusted relationships with technical leaders to drive partner integrations.

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.

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