NVIDIA Logo

NVIDIA

Senior Solutions Architect, Agentic AI

Posted 9 Days Ago
Be an Early Applicant
In-Office or Remote
Hiring Remotely in Santa Clara, CA
184K-288K Annually
Senior level
In-Office or Remote
Hiring Remotely in Santa Clara, CA
184K-288K Annually
Senior level
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.
The summary above was generated by AI

We are looking for a Senior Solutions Architect to help leading Enterprise ISVs design, build, optimize, and deploy production-grade Agentic AI systems on NVIDIA’s accelerated computing platform. In this role, you will partner with strategic software companies to translate frontier AI capabilities into reliable enterprise products, spanning multi-agent orchestration, RAG, tool use, model customization, and production deployment.
 

We work at the intersection of partner engineering, NVIDIA’s AI platform, and product development. You will lead sophisticated technical projects from initial exploration through architecture, prototyping, performance optimization, production rollout, and field enablement. Together, we will help partners adopt NVIDIA technologies and GPU-accelerated infrastructure to bring next-generation AI products to market.
 

What you'll be doing:

  • Lead technical delivery for strategic Agentic AI partner engagements from discovery and architecture through PoC, production readiness, rollout, and scale.

  • Design and build enterprise-grade agentic systems, including multi-agent workflows, tool-using agents, RAG-integrated applications, planning, memory, evaluation, and guardrail patterns.

  • Lead deep architecture reviews with partner engineering teams, driving tradeoffs across model quality, latency, efficiency, cost, retrieval quality, reliability, safety, security, and observability.

  • Build hands-on PoCs, benchmarks, reference architectures, and reusable blueprints that help Enterprise ISVs and NVIDIA field teams move from exploration to production.

  • Guide partners on model customization and post-training workflows, including supervised fine-tuning, reinforcement learning methods, human or AI feedback, direct preference optimization, PEFT/LoRA, synthetic data generation, evaluation, and regression analysis.

  • Work with agent harnesses and execution environments such as OpenShell, OpenAI Agents SDK, LangGraph, LlamaIndex, LangChain, CrewAI, Semantic Kernel, or similar frameworks.

  • Translate partner deployment findings into actionable feedback for NVIDIA Product and Engineering, so we can improve our platforms, tools, and field guidance.

What we need to see:

  • BS/MS/PhD in Computer Science, Electrical Engineering, AI/ML, or equivalent experience.

  • 8+ years of engineering, solutions architecture, applied ML, or technical deployment experience.

  • Consistent track record leading complex AI, ML, distributed systems, or enterprise software deployments from prototype to production.

  • Hands-on experience building LLM, generative AI, RAG, or agentic AI applications in production or production-like environments.

  • Strong programming and debugging skills in Python and Linux environments, with experience in PyTorch, TensorFlow, or similar deep learning frameworks.

  • Deep understanding of agentic AI architectures, including tool use, orchestration, memory, retrieval, planning, evaluation, guardrails, and failure handling.

  • Experience with model customization or post-training techniques such as SFT, RL/RLHF/RLAIF, DPO or relevant equivalent experience, reward modeling, LoRA/PEFT, quantization-aware optimization, or model evaluation.

  • Ability to lead ambiguous partner engagements, influence senior engineering collaborators, and communicate clearly with technical and executive audiences.

Ways to stand out from the crowd:

  • Hands-on experience with NVIDIA AI software such as NIM, NeMo Framework, NeMo Retriever, NeMo Guardrails, NeMo Agent Toolkit, Dynamo, Nemotron, Triton, TensorRT-LLM, or NIM Operator.

  • Experience building post-training pipelines for reasoning, tool use, domain adaptation, enterprise task performance, or agent behavior improvement.

  • Experience with agent harnesses, sandboxed execution, policy enforcement, OpenShell-like environments, or secure enterprise agent runtime build.

  • Recognized expertise in RAG, model customization, agent orchestration, enterprise AI security, or GPU-accelerated AI infrastructure, with field-facing technical presence through workshops, architecture reviews, talks, whitepapers, or developer enablement.

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 20, 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

3 Days Ago
In-Office or Remote
CA, USA
184K-288K Annually
Senior level
184K-288K Annually
Senior level
Artificial Intelligence • Computer Vision • Hardware • Robotics • Metaverse
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.
Top Skills: A2AAi BlueprintsAWSAzureCC++Ci/CdCrewaiCublasCuda-XCudnnDaskDistributed GpuDynamoGCPInfinibandKubernetesLangchainLanggraphLinuxLlamaindexMcpMpiNcclNemo Agent ToolkitNemo FrameworkNemo RetrieverNvidia NimNvlinkOciOpenai Agents SdkOpenshiftPythonPyTorchRapidsSparkTensorrt-LlmTriton Inference Server
An Hour Ago
Remote or Hybrid
United States
60K-120K Annually
Senior level
60K-120K Annually
Senior level
Cloud • Insurance • Payments • Software • Business Intelligence • App development • Big Data Analytics
As a Software Development Engineer in Test, you'll create and conduct automated tests, resolve technical issues, and collaborate with development teams to ensure software quality.
Top Skills: AWSAzureCloud ComputingDockerGCPGqlKubernetesObject-Oriented ProgrammingPlaywrightSQL
An Hour Ago
Remote or Hybrid
United States
115K-185K Annually
Senior level
115K-185K Annually
Senior level
Cloud • Insurance • Payments • Software • Business Intelligence • App development • Big Data Analytics
Lead a new data engineering team to define standards, drive cross-functional AI-driven initiatives, and provide hands-on guidance in SQL optimization, data modeling, and the GCP data/streaming stack. Balance technical leadership with people management, coach engineers, promote AI-assisted workflows, and collaborate with Product and Architecture to build a standardized data ecosystem.
Top Skills: Ai-Assisted Engineering WorkflowsApache BeamBigQueryCloud SqlDatadogGitlab Ci/CdGkeGoGoogle Cloud DataflowPostgresPub/SubPythonRedisSnowflakeSQLTerraform Cdk

What you need to know about the Chicago Tech Scene

With vibrant neighborhoods, great food and more affordable housing than either coast, Chicago might be the most liveable major tech hub. It is the birthplace of modern commodities and futures trading, a national hub for logistics and commerce, and home to the American Medical Association and the American Bar Association. This diverse blend of industry influences has helped Chicago emerge as a major player in verticals like fintech, biotechnology, legal tech, e-commerce and logistics technology. It’s also a major hiring center for tech companies on both coasts.

Key Facts About Chicago Tech

  • Number of Tech Workers: 245,800; 5.2% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: McDonald’s, John Deere, Boeing, Morningstar
  • Key Industries: Artificial intelligence, biotechnology, fintech, software, logistics technology
  • Funding Landscape: $2.5 billion in venture capital funding in 2024 (Pitchbook)
  • Notable Investors: Pritzker Group Venture Capital, Arch Venture Partners, MATH Venture Partners, Jump Capital, Hyde Park Venture Partners
  • Research Centers and Universities: Northwestern University, University of Chicago, University of Illinois Urbana-Champaign, Illinois Institute of Technology, Argonne National Laboratory, Fermi National Accelerator Laboratory

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account