Senior System Software Engineer, Agentic Inference - Dynamo
NVIDIA is hiring a Senior System Software Engineer, Agentic Inference - Dynamo in Santa Clara, United States. It pays $224k-$357k a year and Level rates it ; you can apply on NVIDIA.
Level's read on this job
- On Level's scale, this software engineer role is Builds AI ●●●●: the job is building AI systems.
- Pay on this posting starts 34% higher than the typical software engineer posting on Level.
- The posting mentions Claude, vLLM and Claude Code 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
We are now looking for a Senior System Software Engineer to work on Dynamo. NVIDIA is hiring software engineers for its GPU-accelerated deep learning software team. Academic and commercial groups around the world are using GPUs to power a revolution in AI, enabling breakthroughs in problems from image classification to speech recognition to natural language processing. We are a fast-paced team building Generative AI inference platform to make design and deployment of new AI models easier and accessible to all users.
What you'll be doing:
In this role, you will develop open source software to serve inference of trained AI models running on GPUs.
Contribute to the development of disaggregated serving for Dynamo-supported inference engines (vLLM, SGLang, TRT-LLM) and expand these capabilities to support agentic inference workloads, including long-horizon reasoning, tool calling, and stateful, multi-turn execution.
Innovate in inference-state management for long-running agents, including KV- and prefix-cache reuse and transfer across heterogeneous memory and storage hierarchies with NIXL, to reduce repeated prompt processing, improve latency and token throughput, maximize GPU utilization, and lower per-token and per-task costs for self-hosted LLMs.
Build and evolve Dynamo’s distributed inference frontend across vLLM, SGLang, and TensorRT-LLM, delivering day-0 support for new models, model-specific request parameters, upstream API compatibility, and stateful Responses API semantics.
Balance a variety of objectives: build robust, scalable, high performance software components to support our distributed inference workloads; work with team leads to prioritize features and capabilities; load-balance asynchronous requests across available resources; optimize throughput under latency constraints; and integrate the latest open source technology.
What we need to see:
Masters or PhD or equivalent experience
10+ years in Computer Science, Computer Engineering, or related field
Ability to work in a fast-paced, agile team environment
Excellent Rust/Python programming and software design skills, including debugging, performance analysis, and test design.
Understanding of modern LLM API semantics, including structured outputs, tool calling, reasoning controls, token accounting, context management, and multimodal inputs.
Ways to stand out from the crowd:
Prior contributions to open-source AI inference frameworks (e.g., vLLM, TensorRT-LLM, SGLang).
Experience optimizing GPU memory, KV and prefix caches, or high-performance networking for long-context, reasoning, and tool-calling workloads.
Understanding of LLM-specific inference challenges for agentic workloads, including context and reasoning-token growth, bursty tool-call-driven traffic, multi-turn state reuse, and scheduling across concurrent trajectories.
Prior experience integrating self-hosted LLM serving stacks with agent harnesses such as OpenCode, Codex, Claude Code, and Pi, including compatibility for APIs, streaming, structured outputs, tool calls, and session semantics.
NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most expert and passionate people in the world working for us. Are you creative and autonomous? Do you love a challenge? If so, we want to hear from you. Come help us build the real-time, efficient computing platform driving our success in the multifaceted and quickly growing field Deep Learning and Artificial Intelligence.
#LI-Hybrid
Your base salary will be determined based on your location, experience, and other objective job-related factors. The expected base salary ranges for this position are:224,000 USD – 356,500 USD for Level 5; and 272,000 USD – 431,250 USD for Level 6.
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 System Software Engineer, Agentic Inference - Dynamo at NVIDIA rates 93 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 software engineer jobs at this level
Pay
- This job starts at
- $224k
- Typical software engineer job
- $167k
This posting starts 34% above the typical software engineer job. See software engineer jobs
Questions you could be asked
- What NLP problem have you worked on, and how did you measure whether it actually worked?
- What have you built with speech recognition or text-to-speech, and where did it break?
- What are the limits of Claude that you've run into, and how did you work around them?
- What's a project where you used vLLM hands-on?
- Walk me through how you've used Claude Code in your day-to-day work.
Adapt your resume
- List these exact terms on your resume: NLP, Speech, Claude, vLLM, and Claude Code. 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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