Role at a glance
- Job function
-
Software Engineering & IT Solutions Architecture
- Salary
- Not yet verified Check the description for pay details; an amount or pay period has not been verified.
- Location
- Santa Clara, California, United States
- Work arrangement
- On-site
- Employment
- Full-time
- Experience
- 2+ years as an ML/Software Engineer or Solutions Architect writing production-level code in Python and/or C/C++ in Linux environments.
- Education
- BS/MS/PhD in Computer Science, Electrical/Computer Engineering, Physics, Mathematics, AI/ML, or a related field (or equivalent experience)
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Role Summary
The Executive Briefing Center Solutions Architect develops, demonstrates, and packages agentic AI systems, combining hands-on architecture and coding with customer-facing presentations. The role works with account Solutions Architects and NVIDIA teams to develop proofs of concept and present technical demos.
What You'll Do
- Architect, build, and ship end-to-end agentic AI applications across use cases involving multi-agent coordination, long-horizon...
- Serve as a technical advisor alongside subject matter experts in executive briefings.
- Create and present demos for trade shows and customer meetings.
- Partner with engineering, product, and sales teams to develop proofs of concept, translate customer feedback into product and roadmap...
Generated from the employer's posting. Verify important details before applying.
View full postingQualifications
Requires a BS, MS, or PhD in a relevant field or equivalent experience; 2+ years writing production-level code in Python and/or C/C++ in Linux; experience building agentic and multi-agent AI systems; knowledge of MCP and A2A; and expertise in PyTorch, distributed GPU training, scalable GPU-accelerated architectures, inference optimization, and cloud or on-premise deployment. Strong communication and presentation skills are also required.
Required
- 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,...
- Strong background in PyTorch and distributed GPU (post-)training. Able to quickly prototype and build scalable GPU-accelerated...
- Strong grasp of the way C-Suite and Industry Leaders think paired with excellent communication and presentation skills. Able to explain...
Preferred
- Practical experience working directly with the NVIDIA agentic AI software stack—NVIDIA NIM, NeMo Framework, NeMo Retriever, NeMo Agent...
- Expertise building LLM evaluation harnesses, benchmarking systems, observability platforms, and safety guardrails, plus fine-tuning and...
- Experience developing production-grade deployment patterns using Kubernetes/OpenShift, CI/CD automation, and secure cloud-native...
- Proven experience handling NVIDIA GPU architectures, CUDA-X libraries (cuBLAS, cuDNN, RAPIDS), and HPC technologies (NCCL, InfiniBand,...
- A strong public profile (blogs, GitHub, conference talks) that demonstrates your expertise and passion for agentic AI.
Original job description
Content provided by the employer
Original job description
Content provided by the employer
NVIDIA’s Executive Briefing Center (EBC) Solutions Architect (SA) team is looking for a highly hands-on Solutions Architect with exemplary communication skills. The role involves developing, demonstrating (in the NVIDIA EBC), and packaging agentic AI systems. Partnering with account SAs you will co-develop proof of concepts (POC) and "uplift" their presentation quality to match the NVIDIA branding and messaging used with Executive meetings.
This is a builder’s and presenter's role! You will spend time architecting and writing code. You will develop multi-agent systems, retrieval pipelines, and optimized inference stacks on NVIDIA’s full-stack accelerated computing platform. We want a creative, diligent, and curious engineer energized by agentic AI and ready to make significant change. If that’s you, join us!
What you’ll be doing:
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.
What we need to see:
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.
You will also be eligible for equity and benefits.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive 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.About the company
NVIDIA
Large Enterprise
NVIDIA is a leading technology company renowned for its graphics processing units (GPUs) and innovative computing solutions that enhance visual experiences across multiple platforms, including gaming, scientific research, and artificial intelligence. Founded in 1993, the company has expanded its offerings to include powerful AI frameworks and deep learning platforms, making significant contributions to industries such as gaming, data centers, automotive, and healthcare. NVIDIA's commitment to pushing the boundaries of visual computing continues to drive advancements in both hardware and software, positioning the company at the forefront of emerging technologies and digital transformation.