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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.
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.
Ways to stand out from the crowd:
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.
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.
You will also be eligible for equity and .
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