Senior Developer Technology Engineer - Edge Agentic AI

NVIDIA NVIDIA · Semiconductors · Santa Clara, CA

Senior Developer Technology Engineer focused on enabling and optimizing agentic AI workflows at the edge using NVIDIA's platforms. This role involves working with internal and external partners on deployment challenges, profiling, debugging, and improving LLM/GenAI user experience through open-source software enhancements. It also includes providing technical leadership and collaborating with hardware and research teams.

What you'd actually do

  1. Work 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.
  2. 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.
  3. 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.
  4. 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.
  5. 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.

Skills

Required

  • 5+ years of professional experience in local GPU deployment, profiling and optimization
  • 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
  • Strong problem-solving skills
  • Ability to work both independently and collaboratively in a fast-paced environment
  • Excellent interpersonal and communication skills

Nice to have

  • 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

What the JD emphasized

  • local end-to-end agentic AI GPU deployment challenges
  • accelerated end-to-end agentic AI workflows
  • efficient end-to-end agentic AI deployment
  • agentic AI

Other signals

  • enabling agentic AI workflows
  • deploying LLMs and GenAI
  • optimizing inference performance