Role at a glance
- Salary
- $184K – $287.5K/yr
- Location
- Santa Clara, California, United States
- Work arrangement
- On-site
- Employment
- Full-time
- Experience
- 8+ 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
This Solutions Architect role on NVIDIA’s Solutions Architect team focuses on developing and deploying agentic AI systems with Media & Entertainment companies across studios, streaming, broadcast, gaming, advertising, content creation, and media supply chain organizations. The role turns large language model capabilities into production-scale agents that support content creation, personalization, distribution, and monetization.
What You'll Do
- Architect, build, and ship end-to-end agentic AI applications and high-performance RAG pipelines for heterogeneous media assets.
- Act as a hands-on technical advisor and domain expert during pre-sale and post-sale engagements with customer AI researchers, engineers,...
- Optimize inference performance and total cost of ownership using NVIDIA’s AI inference stack.
- Build proofs of concept, reference architectures, and reusable blueprints for production deployment.
- Partner with NVIDIA engineering, product, and sales teams to translate customer feedback into product and roadmap insights and scale...
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View full postingQualifications
BS/MS/PhD or equivalent experience in a relevant technical field; 8+ years of production-level coding experience in Python and/or C/C++ in Linux environments; experience building agentic and multi-agent AI systems; strong background in PyTorch and distributed GPU training; deployment experience at scale on public cloud or on-premise; strong M&E industry knowledge and communication skills.
Required
- Production-level coding in Python and/or C/C++ in Linux environments
- Building sophisticated agentic and multi-agent AI systems using orchestration frameworks such as LangGraph, LlamaIndex, CrewAI,...
- Understanding of MCP and A2A
- PyTorch and distributed GPU (post-)training
- Test-time compute, reinforcement learning, inference optimization, and post-training
- Deployment of workloads at scale on AWS, GCP, Azure, OCI, or on-premise
- M&E industry knowledge
- Communication and presentation skills
Preferred
- NVIDIA NIM
- NeMo Framework
- NeMo Retriever
- NeMo Agent Toolkit
- Dynamo
- Triton Inference Server
- TensorRT-LLM
- AI Blueprints
Original job description
Content provided by the employer
Original job description
Content provided by the employer
NVIDIA’s Solutions Architect team is looking for a senior, highly hands-on Solutions Architect. The role involves developing, building, and deploying agentic AI systems with top Media & Entertainment (M&E) companies. Partnering with customers from studios, streaming and broadcast platforms, gaming, advertising, content creation, and the media supply chain, you will transform frontier large language model (LLM) capabilities into autonomous agents at production scale. These agents will redefine how content is created, personalized, distributed, and monetized.
This is a builder’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 M&E use cases—spanning multi-agent coordination, long-horizon reasoning, planning, and tool use—along with high-performance RAG pipelines over heterogeneous media assets (text, code, images, audio, video) to tackle real production challenges such as content generation, localization, metadata enrichment, personalization, recommendation, and ad operations.
Act as a hands-on technical advisor and main domain expert during the pre- and post-sale stages. Work closely with customer AI researchers, engineers, and developers to build, prototype, and deploy Agentic solutions on NVIDIA platforms.
Optimize inference performance and total cost of ownership using the full NVIDIA AI inference stack—and build hands-on proofs-of-concept, reference architectures, and reusable blueprints that serve as production templates and accelerate time-to-value. Post-training open sourced models to meet the M&E requirements.
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)
8+ 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 M&E industry paired with excellent communication and presentation skills. Able to explain sophisticated ideas to both technical and non-technical groups. Works well with executives, partners, and engineering teams. 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.
Widely considered to be one of the technology world’s most desirable employers, NVIDIA offers highly competitive salaries and a comprehensive benefits package. As you plan your future, see what we can offer to you and your family www.nvidiabenefits.com/
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.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.
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.