Solutions Architect, Inference Deployments
NVIDIA is hiring a Solutions Architect, Inference Deployments in Santa Clara, United States. It pays $152k-$242k a year and Level rates it ; you can apply on NVIDIA.
Level's read on this job
- Works on AI ●●●○ is how Level rates this solutions architect role: the daily work is on AI products, without building the model.
- Tools and skills the posting cites include vLLM and AI agents.
- Level classifies it as a senior role.
- Level lists 2,700+ other open roles at NVIDIA.
AI in this role
NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people.
Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world.
What you'll be doing:
- Lead architecture discussions with customers and co-design scalable inference systems with product and engineering teams. Define technical direction, integration milestones, and deployment plans across edge and cloud environments.
- Deploy, test, and profile speech and action models for robotics and automation on edge devices. Optimize latency, throughput, and memory use within device constraints.
- Lead optimization of synthetic data workflows spanning generation, augmentation, filtering, and data movement. Improve throughput and cost per usable output while preserving data quality.
- Guide production inference deployments, including configuration, monitoring, capacity planning, performance testing, release validation, and rollback. Resolve complex issues across models, runtimes, and infrastructure.
- Evaluate model optimization methods, including quantization, kernel selection, and batching. Validate application quality, explain performance tradeoffs, and use findings to inform product and engineering priorities.
- Drive customer and field enablement through deployment recipes, demos, onboarding materials, and operating guides that help teams adopt and scale NVIDIA technologies.
What we need to see:
- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field, or equivalent experience.
- 5+ years of professional experience in software or hardware engineering, developer relations, technical partnerships, solutions architecture, or product management, including 3+ years of direct, hands-on experience in AI inference or ML systems.
- Deep expertise in AI/ML and GPU inference, with a track record of driving product integrations and delivering production systems across edge or cloud environments.
- Hands-on experience building AI agents and working with Linux systems, containers, and at least one inference runtime or ML framework.
- Demonstrated expertise in performance profiling and production deployment, including monitoring and troubleshooting. Ability to design repeatable benchmarks that measure performance and application quality.
- Ability to explain complex technical concepts clearly to technical and non-technical audiences, from engineers to C-level executives.
- Strong problem-solving skills, intellectual curiosity, and a commitment to learning and helping customers resolve complex technical challenges.
- A track record of building trusted customer and partner relationships, balancing their needs, and guiding complex product and architecture decisions.
Ways to stand out from the crowd:
- Technical contributions that demonstrate clear approaches to complex problems and measurable improvements in performance or production reliability.
- A history of enabling customer adoption, with technical recommendations that influenced product or engineering decisions and delivered production results.
- Hands-on experience with NVIDIA Jetson, TensorRT Edge-LLM, Nemotron Speech, NVIDIA Riva, ROS 2, or NVIDIA Isaac in voice or robotics deployments.
- Experience with synthetic data generation or workflow orchestration using NVIDIA Cosmos or comparable tools.
- Experience with containerized inference, TensorRT-LLM, TensorRT, Triton Inference Server, vLLM, SGLang, or NVIDIA Dynamo.
NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. If you're creative and autonomous, we want to hear from you!
152,000 USD – 241,500 USD for Level 3; and 184,000 USD – 287,500 USD for Level 4.
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
Solutions Architect, Inference Deployments at NVIDIA rates 66 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.
Works on AI. The daily work is on AI products, without building the model.
- ●●●● 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
- $152k
- Typical solutions architect job
- $169k
This posting starts 10% below the typical solutions architect job. See solutions architect jobs
Questions you could be asked
- How do you decide when an AI agent can act on its own versus asking for approval first?
- Walk me through how you've used vLLM in your day-to-day work.
- Describe a typical day in a role like this one: which parts run through AI directly?
- If you removed AI from this role, what would be left, and how do you decide what still needs a human?
Adapt your resume
- List these exact terms on your resume: AI agents and vLLM. 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.
- Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.
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