NVIDIA Logo

NVIDIA

Senior Solutions Architect, Agentic AI

Posted 5 Days Ago
Be an Early Applicant
In-Office or Remote
Hiring Remotely in CA, USA
184K-288K Annually
Senior level
In-Office or Remote
Hiring Remotely in CA, USA
184K-288K Annually
Senior level
Architect, prototype, and deploy production-grade agentic and multi-agent AI systems for Media & Entertainment. Build high-performance RAG pipelines over multi-modal assets, optimize GPU inference and TCO on NVIDIA platforms, advise customers pre/post-sale, and create reusable reference architectures, blueprints, and technical collateral to scale solutions.
The summary above was generated by AI

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.

Applications for this job will be accepted at least until July 26, 2026.

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.

Similar Jobs

11 Days Ago
In-Office or Remote
184K-288K Annually
Senior level
184K-288K Annually
Senior level
Artificial Intelligence • Computer Vision • Hardware • Robotics • Metaverse
Lead partner engagements to design, prototype, and deploy production-grade agentic AI systems on NVIDIA GPUs. Architect multi-agent workflows, RAG, tool use, planning, memory, evaluation, and guardrails; build PoCs, benchmarks, and reference architectures; optimize performance and cost; guide model customization and post-training workflows; use agent harnesses and translate findings to product and engineering teams for platform improvement and field enablement.
Top Skills: CrewaiDpoDynamoGpu-Accelerated InfrastructureLangchainLanggraphLinuxLlamaindexLlmLora/PeftNemo Agent ToolkitNemo FrameworkNemo GuardrailsNemo RetrieverNemotronNimNim OperatorOpenai Agents SdkOpenshellPythonPyTorchQuantization-Aware OptimizationRagRlRlaifRlhfSemantic KernelSftTensorFlowTensorrt-LlmTriton
An Hour Ago
Remote or Hybrid
CA, USA
149K-223K Annually
Mid level
149K-223K Annually
Mid level
eCommerce • Fintech • Hardware • Payments • Software • Financial Services
Field-driven territory sales role responsible for full-cycle, self-sourced selling: prospecting, delivering live demos, closing deals, and building pipeline through door-to-door outreach, partnerships, and events. Spend most weeks in-market, manage Salesforce activity, master verticals (restaurants, retail, services), and consistently exceed quota while ensuring smooth onboarding and strong local presence.
Top Skills: Salesforce
An Hour Ago
In-Office or Remote
130K-150K Annually
Senior level
130K-150K Annually
Senior level
Greentech • Hardware • Internet of Things • Machine Learning • Software • Business Intelligence • Agriculture
Lead full-cycle recruiting for GTM and other functions, build scalable hiring processes and pipelines, partner with hiring managers on workforce planning, improve candidate experience and employer brand, track hiring metrics, support compensation benchmarking, DEI hiring practices, and enable managers through coaching and training.
Top Skills: Ats

What you need to know about the NYC Tech Scene

As the undisputed financial capital of the world, New York City is an epicenter of startup funding activity. The city has a thriving fintech scene and is a major player in verticals ranging from AI to biotech, cybersecurity and digital media. It also has universities like NYU, Columbia and Cornell Tech attracting students and researchers from across the globe, providing the ecosystem with a constant influx of world-class talent. And its East Coast location and three international airports make it a perfect spot for European companies establishing a foothold in the United States.

Key Facts About NYC Tech

  • Number of Tech Workers: 549,200; 6% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: Capgemini, Bloomberg, IBM, Spotify
  • Key Industries: Artificial intelligence, Fintech
  • Funding Landscape: $25.5 billion in venture capital funding in 2024 (Pitchbook)
  • Notable Investors: Greycroft, Thrive Capital, Union Square Ventures, FirstMark Capital, Tiger Global Management, Tribeca Venture Partners, Insight Partners, Two Sigma Ventures
  • Research Centers and Universities: Columbia University, New York University, Fordham University, CUNY, AI Now Institute, Flatiron Institute, C.N. Yang Institute for Theoretical Physics, NASA Space Radiation Laboratory

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account