2 days ago
Santa Clara, CA, USAMid Level / Senior
H1B sponsor
Base Salary
$124k - $242k/yr
Responsibilities
- Architect, build, and ship end-to-end agentic AI applications spanning multi-agent coordination, long-horizon reasoning, planning, and tool use.
- Develop multi-agent systems, retrieval pipelines, and optimized inference stacks on NVIDIA’s accelerated computing platform.
- Act as a technical advisor and subject matter expert during executive briefings.
- Create and present demonstrations for trade shows and customer meetings.
- Partner with account Solutions Architects and NVIDIA engineering, product, and sales teams on proof-of-concept development and build wins.
- Translate customer feedback into product and roadmap insights and scale technical expertise through collateral, workshops, and developer communities.
Requirements
- Bachelor’s, master’s, or doctoral degree in Computer Science, Electrical/Computer Engineering, Physics, Mathematics, AI/ML, or a related field, or equivalent experience.
- At least 2 years of experience as an ML/Software Engineer or Solutions Architect writing production-level code in Python and/or C/C++ in Linux environments.
- Validated experience building sophisticated agentic and multi-agent AI systems with orchestration frameworks such as LangGraph, LlamaIndex, CrewAI, LangChain, or OpenAI Agents SDK, including tool-using and routing agents.
- Strong understanding of MCP and A2A, PyTorch, distributed GPU post-training, test-time compute, reinforcement learning, inference optimization, and post-training.
- Experience prototyping scalable GPU-accelerated architectures and deploying workloads at scale on AWS, GCP, Azure, OCI, or on-premise environments.
- Excellent communication and presentation skills, with the ability to explain sophisticated concepts to technical and non-technical audiences and lead projects end to end.
- Preferred experience with NVIDIA’s agentic AI software stack, LLM evaluation and benchmarking systems, observability, safety guardrails, fine-tuning, quantization, Kubernetes/OpenShift, secure cloud-native infrastructure, NVIDIA GPUs, CUDA-X libraries, HPC technologies, Spark, Dask, and distributed or parallel computing.
- A strong public technical profile through blogs, GitHub, or conference talks is preferred.
Benefits
- Equity and benefits are provided.
- Base salary varies by location, experience, and other objective job-related factors.
- The listed salary ranges cover Level 2 and Level 3 positions.
- Applications are accepted at least until November 3, 2026.
Tech Stack
Categories
Solutions Engineering
About Nvidia
Nvidia designs and sells GPUs and accelerated computing platforms for data centers, AI/ML, graphics, gaming, and automotive, monetizing through hardware, software platforms (CUDA, AI frameworks), and systems like DGX and networking. Customers include cloud providers, enterprises, researchers, and OEMs. Founded in 1993 and headquartered in Santa Clara, it is a public company traded on NASDAQ under NVDA.