NVIDIA's Executive Briefing Center (EBC) Solutions Architect

• Architect, build, and ship end-to-end Agentic AI applications for a variety of use cases-spanning multi-agent coordination, long-horizon reasoning, planning, and tool use.
• Act as Technical Advisor alongside fellow Subject Matter Experts (SME) in Executive Briefings.
• Creating and presenting demos that are used at Trade Shows or Customer Meetings.
• Partner with NVIDIA engineering, product, and sales teams to secure build wins, translate customer feedback into actionable product and roadmap insights, and scale global expertise through technical collateral, workshops, and developer communities.

• BS/MS/PhD in Computer Science, Electrical/Computer Engineering, Physics, Mathematics, AI/ML, or a related field (or equivalent experience)
• 2+ years 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 using orchestration frameworks such as LangGraph, LlamaIndex, CrewAI, LangChain, OpenAI Agents SDK -including tool-using and routing agents. Solid understanding of MCP and A2A is vital.
• Strong background in PyTorch and distributed GPU (post-)training. Able to quickly prototype and build scalable GPU-accelerated architectures. Applies test-time compute, reinforcement learning, inference optimization, and post-training. Deploys workloads at scale on public cloud (AWS, GCP, Azure, OCI) or on-premise.
• Strong grasp of the way C-Suite and Industry Leaders think paired with excellent communication and presentation skills. Able to explain sophisticated ideas to both technical and non-technical groups. Leads projects from start to finish in a fast-paced, multitasking setting.

Ways to stand out from the crowd:

• Practical experience working directly with the NVIDIA agentic AI software stack-NVIDIA NIM, NeMo Framework, NeMo Retriever, NeMo Agent Toolkit, Dynamo, Triton Inference Server, TensorRT-LLM, and AI Blueprints.
• Expertise building LLM evaluation harnesses, benchmarking systems, observability platforms, and safety guardrails, plus fine-tuning and optimizing reasoning-focused LLMs and SLMs through timely engineering and quantization.
• Experience developing production-grade deployment patterns using Kubernetes/OpenShift, CI/CD automation, and secure cloud-native infrastructure, with familiarity with modern agent architectures and emerging communication protocols such as MCP (Model Context Protocol) or Google A2A.
• Proven experience handling NVIDIA GPU architectures, CUDA-X libraries (cuBLAS, cuDNN, RAPIDS), and HPC technologies (NCCL, InfiniBand, MPI, NVLink), along with familiarity in large-scale data processing and distributed/parallel computing frameworks (e.g., Spark, Dask).
• A strong public profile (blogs, GitHub, conference talks) that demonstrates your expertise and passion for agentic AI.

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 124,000 USD - 195,500 USD for Level 2, and 152,000 USD - 241,500 USD for Level 3.