Full-Time

Senior GenAI Engagement Lead

Partner Platforms

NVIDIA

NVIDIA

10,001+ employees

Designs GPUs and AI HPC platforms

Compensation Overview

$184k - $287.5k/yr

+ Equity

Company Historically Provides H1B Sponsorship

Canada + 2 more

More locations: Santa Clara, CA, USA | United States

Hybrid

Category
Sales & Solution Engineering (1)
Required Skills
LLM
Kubernetes
Microsoft Azure
Python
Neural Networks
Pytorch
Docker
RAG
AWS
LangChain
Google Cloud Platform
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 in a customer-facing role.
  • 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 of large projects.
  • Strong understanding of enterprise deployments including MLOps, Cloud Native technologies such as Kubernetes, Docker, Kubeflow, and Enterprise IT environments including Security, Compliance, Governance, Data infrastructure, and Deployments across on-prem, hybrid, and multi-cloud platforms.
  • Strong executive-caliber communication, and deep curiosity for emerging AI technologies. High ownership and initiative, keeping internal and external collaborators aligned.
Responsibilities
  • Build and drive the technical integration of 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. You will 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.
Desired Qualifications
  • Track record of influencing sophisticated product decisions through trusted partner relationships, showing empathy for customer needs and an instinct for translating those into scalable platform improvements.
  • Proactive in anticipating market trends, and advocating for innovation inside and outside the org, with an in-depth knowledge of the ISV and cloud provider landscape.
  • Demonstrated agility in high-stakes environments required to deliver successful outcomes with partner collaborations especially with high-velocity GenAI landscape.
  • Strong growth and solution outlook, highly collaborative standout colleague, able to build deep trust with engineers, executives, and multi-functional teams at both NVIDIA and Partner organizations.

NVIDIA designs and manufactures graphics processing units (GPUs) and computing platforms used for gaming, data centers, and artificial intelligence. These products work by using parallel processing to handle complex mathematical calculations much faster than standard computer processors, supported by a software ecosystem that allows developers to build and run AI models. Unlike competitors that may focus solely on hardware, NVIDIA integrates its chips with specialized software and cloud services to create a complete environment for high-performance tasks. The company’s goal is to provide the underlying technology necessary to power advanced computing, from realistic video game graphics to autonomous vehicles and large-scale data analysis.

Company Size

10,001+

Company Stage

IPO

Headquarters

Santa Clara, California

Founded

1993

Simplify Jobs

Simplify's Take

What believers are saying

  • Data centers generate 89% of $215.9B FY2026 revenue.
  • $40B acquisitions like OpenAI bolster AI infrastructure dominance.
  • Nemotron models and Drive Thor accelerate agentic AI adoption.

What critics are saying

  • AMD MI450X outperforms Blackwell by 25% per watt in inference.
  • Huawei Ascend 910D blocks $10B China AI sales due to bans.
  • Google TPU v6 cuts hyperscaler GPU dependency by 60%.

What makes NVIDIA unique

  • NVIDIA invented GPU in 1999, pioneering accelerated computing.
  • CUDA platform from 2006 enables GPUs for AI and HPC.
  • Holds 92% discrete GPU market share as of Q1 2025.

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Benefits

Company Equity

401(k) Company Match

Growth & Insights and Company News

Headcount

6 month growth

-1%

1 year growth

-3%

2 year growth

-2%
The Associated Press
Apr 15th, 2026
Matlantis integrates NVIDIA ALCHEMI Toolkit for 10x faster materials simulation

Matlantis has integrated NVIDIA's ALCHEMI Toolkit into its materials simulation platform to accelerate industrial materials discovery. The company previously incorporated NVIDIA Warp-optimised kernels, achieving up to 10x speed improvements in atomistic calculations. The integration includes LightPFP, Matlantis' lightweight potential for large-scale simulations, which uses a server-based architecture with NVIDIA ALCHEMI Toolkit-Ops to reduce communication bottlenecks. Matlantis plans to integrate its flagship Universal Machine-Learning Interatomic Potential with the toolkit to further enhance GPU efficiency. Launched in 2021, Matlantis is a cloud-based atomistic simulator jointly developed by PFN and ENEOS. The platform uses deep learning to increase simulation speeds by tens of thousands of times and serves over 150 companies discovering materials including catalysts, batteries and semiconductors.

CNBC
Apr 14th, 2026
Nvidia stock surges 18% on 10-day winning streak fuelled by $1T GPU orders through 2027

Nvidia shares have climbed 18% over a ten-day winning streak, the longest since 2023. The stock is trading about 8% below its October all-time high of $212.19. CEO Jensen Huang revealed at last month's GTC conference that Nvidia has over $1 trillion in GPU orders through 2027, including Blackwell and next-generation Vera Rubin chips. Data centre revenue surged 75% year-over-year and now comprises 88% of the business, a dramatic shift from five years ago when gaming dominated. The rally follows major deals including Meta's February commitment to deploy millions of Nvidia chips across its global data centres. On Monday, Nvidia denied rumours it was pursuing acquisitions of PC makers Dell or HP. The company also unveiled Ising, a new family of open-source models for quantum computing.

Yahoo Finance
Apr 14th, 2026
D-Wave CEO claims quantum computers could challenge Nvidia's AI dominance with superior power efficiency

D-Wave Quantum CEO Alan Baratz claims quantum computing poses a threat to Nvidia, citing superior energy efficiency. Speaking at the Semafor World Economy Summit, Baratz said D-Wave's quantum computer uses just 10 kilowatts of power—equivalent to five or 10 GPUs—whilst solving problems that would take GPU systems nearly a million years. D-Wave shares rose nearly 16% on Tuesday, part of a 140% gain over the past year. The company reported $2.75 million in Q4 revenue, missing analyst estimates, but bookings surged 471% to $13.4 million. The $5.3 billion company recently secured a $20 million agreement with Florida Atlantic University and acquired Quantum Circuits for $550 million. However, quantum machines remain specialised tools, unable to run large language models that drive Nvidia's dominance.

Yahoo Finance
Apr 14th, 2026
Vertiv partners with Nvidia on AI data centre infrastructure as analysts raise price target to $300

Vertiv Holdings has been reaffirmed with a Buy rating by Evercore ISI, setting a price target of $280, whilst Barclays raised its target from $281 to $300 with an Overweight rating. The electrical equipment company is partnering with Nvidia on AI infrastructure development. On 16th March, Nvidia introduced its Vera Rubin DSX AI Factory reference design, with Vertiv providing critical power and cooling solutions for AI data centres. The partnership integrates Vertiv's infrastructure expertise with Nvidia's AI systems to enhance energy efficiency and performance. Vertiv is developing Vertiv OneCore Rubin DSX, a prefabricated system designed to accelerate AI factory deployment. The Brussels-headquartered company specialises in critical digital infrastructure technologies for data centres and communication networks.

Yahoo Finance
Apr 14th, 2026
Nvidia and Dell: AI infrastructure stocks to buy ahead of May earnings

Nvidia and Dell Technologies are positioned as attractive AI infrastructure investments ahead of their May earnings reports, according to recent analysis. Both companies supply critical hardware for AI computing, with demand for AI capacity continuing to outpace available resources across major cloud services. Nvidia shares have remained flat for six months despite strong fundamentals. Last quarter, its data centre business generated $62 billion in revenue, up 75% year over year, with a 75% gross margin. The company expects over $1 trillion in cumulative orders for its Blackwell and upcoming Rubin chips through 2027. Trading at 17 times next year's expected earnings, Nvidia's valuation appears discounted relative to its 66% revenue growth in fiscal year 2026. Dell Technologies similarly stands to benefit from the AI infrastructure build-out. Both companies report earnings in May.