Senior GenAI Technical Lead, Partner Platforms

Reposted 5 Days Ago
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Hiring Remotely in Santa Clara, CA, USA
In-Office or Remote
184K-357K Annually
Senior level
Artificial Intelligence • Computer Vision • Hardware • Robotics • Metaverse
The Role
Lead the technical integration of GenAI offerings with enterprise ISVs and cloud service providers, shaping software design and developer experience while ensuring adoption across use cases.
Summary Generated by Built In

NVIDIA's Enterprise Product Group is seeking a highly technical GenAI Product Integration Lead to define and implement the technical strategy for integrating our Generative AI software with our most strategic enterprise ISV and CSP partners. As the key technical driver for your assigned partners, you will build trusted relationships with their Platform Architects and accelerate the adoption of NVIDIA's offerings across critical enterprise initiatives!

This role demands versatility to operate proficiently at the intersection of platform strategy, strong hands-on technical execution, and business acuity with senior leaders, staying ahead of the advancements in Generative and Agentic AI. You will influence product direction, infrastructure investments, and ensure the deployment of robust, scalable GenAI solutions that redefine enterprise capabilities.

What You Will Be Doing:

  • 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. 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.

What we need to see:

  • 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 collaboration 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.

Ways to Stand Out from the crowd:

  • Track record of influencing complex 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 is widely considered to be one of the technology world’s most desirable employers. We have some of the most brilliant, forward-thinking and hardworking people in the world working for us. There has never been a more exciting time to join!

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until May 31, 2026.

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.

Skills Required

  • 8+ years of proven experience in technical Product or Engineering roles
  • Masters or PhD in Computer Science, Electrical Engineering or equivalent experience
  • Strong background in AI/ML and Deep Learning with hands-on experience
  • Experience with programming languages and libraries such as Python, PyTorch, and HuggingFace
  • Strong understanding of enterprise deployments including MLOps and Cloud Native technologies

NVIDIA Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NVIDIA and has not been reviewed or approved by NVIDIA.

  • Equity Value & Accessibility Equity awards and a discounted ESPP are highlighted as core parts of total compensation, enabling employees to share in the company’s success. Stock-based compensation and the two-year lookback ESPP are consistently described as especially valuable.
  • Healthcare Strength Health coverage is portrayed as robust, with comprehensive medical, dental, and vision options alongside mental health support and on-site care resources. Employer HSA contributions and wellness perks reinforce the depth of the offering.
  • Retirement Support Retirement programs are depicted as strong, featuring a meaningful 401(k) match with Roth options and support for Mega Backdoor Roth contributions. These elements position long-term savings as a notable advantage of the total rewards package.

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The Company
HQ: Santa Clara, CA
21,960 Employees
Year Founded: 1993

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.”

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