Senior Solutions Architect, Agentic AI
NVIDIA is hiring a Senior Solutions Architect, Agentic AI in Santa Clara, United States. It pays $184k-$288k a year and Level rates it ; you can apply on NVIDIA.
Level's read on this job
- On Level's scale, this solutions architect role is Builds AI ●●●●: the job is building AI systems.
- Pay on this posting starts 9% higher than the typical solutions architect posting on Level.
- The posting mentions OpenAI, LangChain and LlamaIndex among its tools and skills.
- Level classes it as a senior role.
- NVIDIA has 2,600+ other open roles on Level.
AI in this role
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 other objective job-related factors. The expected base salary range for this position 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 November 3, 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.How we rate this
Senior Solutions Architect, Agentic AI at NVIDIA rates 99 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Also common in solutions architect jobs at this level
Pay
- This job starts at
- $184k
- Typical solutions architect job
- $169k
This posting starts 9% above the typical solutions architect job. See solutions architect jobs
Questions you could be asked
- How would you design a retrieval step so the model answers from real data instead of guessing?
- Walk me through fine-tuning a model: what data did you use, and how did you check the result?
- How do you decide that one model's output is better than another's for a given task?
- What's a project where you used OpenAI hands-on?
- Walk me through how you've used LangChain in your day-to-day work.
Adapt your resume
- List these exact terms on your resume: RAG, Fine-tuning, AI Evaluation, OpenAI, and LangChain. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
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