Senior Developer Technology Engineer - Edge Agentic AI
NVIDIA is hiring a Senior Developer Technology Engineer - Edge Agentic AI 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
- On Level's scale, this role is Builds AI ●●●●: the job is building AI systems.
- The posting mentions Llama, Ollama and vLLM among its tools and skills.
- Level classes it as a senior role.
- NVIDIA has 2,700+ other open roles on Level.
AI in this role
Design and optimize edge agentic AI workflows and LLM deployment on NVIDIA RTX and DGX platforms.
At NVIDIA, 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.
As a Developer Technology Engineer, you will be at the forefront of innovation, working with leading industry partners and pioneering open-source projects to enable professional agentic AI workflows at the edge powered by NVIDIAs RTX and DGX platforms. This role offers an outstanding opportunity to collaborate with world-class talent and make a significant contribution to the evolving landscape of enterprise and consumer agentic AI.
What you'll be doing:
Work closely across internal engineering and product teams as well as external app developers and enterprise ISVs on solving local end-to-end agentic AI GPU deployment challenges on NVIDIA RTX & DGX.
Apply powerful profiling and debugging tools for analyzing most demanding accelerated end-to-end agentic AI workflows to detect insufficient system utilization resulting in suboptimal runtime performance.
Conduct hands-on trainings, develop sample code and host presentations to give good guidance on efficient end-to-end agentic AI deployment targeting optimal runtime performance.
Improve LLM & GenAI user experience by working on feature and performance enhancements of OSS software, including but not limited to projects like GGML, Llama.cpp, Ollama, vLLM, ONNX Runtime.
Collaborate with GPU driver and architecture teams as well as NVIDIA research to influence next generation GPU features by providing real-world workflows and giving feedback on partner and customer needs.
Providing technical leadership and mentorship to junior engineers, encouraging an inclusive and high-performing team environment.
What we need to see:
A proven track record 5+ years of professional experience in local GPU deployment, profiling and optimization.
A Bachelor's or Master's degree or equivalent experience in Computer Science, Engineering, or a related field.
Strong proficiency in C/C++, Python, software design, programming techniques..
Familiarity with and development experience on Windows and Linux.
Experience with CUDA and NVIDIA's Nsight GPU profiling and debugging suite.
Some travel is required for conferences and for on-site visits with external partners.
Strong problem-solving skills and the ability to work both independently and collaboratively in a fast-paced environment.
Excellent interpersonal and communication skills and a passion for keeping track with the latest advancements in AI technology.
Ways to stand out from the crowd:
Experience with GPU-accelerated AI inference driven by NVIDIA APIs and SDKs, specifically TensorRT-RTX, cuDNN, NVIDIA Model Optimizer.
Expertise with professional agentic AI use cases, i.e., digital content creation and productivity workflows.
Experience working with open-source LLM and GenAI software.
Detailed knowledge of the latest generation GPU architectures.
Experience with AI deployment on NPUs and ARM architectures.
Widely considered to be one of the technology world’s most desirable employers, NVIDIA offers highly competitive salaries and a comprehensive benefits package. We have some of the most forward-thinking and hardworking people in the world working for us. If you're creative, autonomous and love a challenge, we want to hear from you.
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 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 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.How we rate this
Senior Developer Technology Engineer - Edge Agentic AI at NVIDIA rates 90 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
Questions you could be asked
- Tell me about a project where gpu deployment was part of your work. What did you do?
- Tell me about a project where profiling was part of your work. What did you do?
- Tell me about a project where optimization was part of your work. What did you do?
- Tell me about a project where llm was part of your work. What did you do?
- Tell me about a project where genai was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: GPU Deployment, Profiling, Optimization, LLM, and GenAI. 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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