Software Engineer, OpenShell
NVIDIA is hiring a Software Engineer, OpenShell for a remote role open to applicants in United States. It pays $184k-$288k a year and Level rates it ; you can apply on NVIDIA.
Level's read on this job
- Builds AI ●●●● is how Level rates this software engineer role: the job is building AI systems.
- The listed pay starts 10% above the typical software engineer posting on Level.
- The posting lists this role as remote.
- Tools and skills the posting cites include vLLM, AI agents and AI research.
- Level lists 2,700+ other open roles at NVIDIA.
AI in this role
Are you ready to translate groundbreaking AI research into secure, production-grade systems? Want to shape the next generation of AI agent infrastructure? Join us!
At NVIDIA OpenShell, we are building the runtime infrastructure for secure, scalable, production-grade AI agents. As an OpenShell Research Engineer, we will look to you to help bring the latest advances in agentic systems into the runtime, tools, and workflows that enterprise builders rely on.
This role sits at the intersection of research, product, and engineering. We expect you to identify promising methods from academia, industry, open source, and internal NVIDIA research, understand where they matter for OpenShell, validate their impact through hands-on prototypes, benchmarks, and real agent workflows, and help us integrate the best ideas into the product.
What You’ll be Doing:
Track the cutting edge: How are agentic systems evolving? You'll follow research in tool use, planning, memory, evaluation, self-improvement, multi-agent workflows, runtime infrastructure, and agent safety/security.
Bridge research and product: Identify research ideas that can meaningfully improve OpenShell and translate them into concrete product opportunities.
Benchmark and adapt: Reproduce and test promising methods from papers, open-source projects, industry work, and internal NVIDIA research.
Build rapid prototypes: Create hands-on proof-of-concepts using OpenShell, including agent harnesses, evaluation loops, self-improving workflows, and runtime-native developer experiences.
Red-team systems: Design evaluation and red-team harnesses that measure agent reliability, usefulness, scalability, safety, security, and developer experience.
Secure the workflow: Help us design secure-by-default workflows for agents operating with tools, code, files, credentials, and enterprise systems.
Partner across teams: Collaborate closely with engineering, product, design, research, solutions, and developer-facing teams to move ideas from prototype to product.
What you’ll need:
8+ years of professional practical experience in research engineering, software development, or a related technical field
MS/PhD in Computer Science, Physics, or a related field or equivalent experience
A strong background in turning complex research into reusable products, tools, demos, benchmarks, or production systems at scale.
Deep experience in several of the following: LLMs, agent harnesses, multimodal generative models, evaluation frameworks, synthetic data generation, post-training, inference infrastructure/optimization, adversarial ML, or agent safety/security.
Demonstrated ability to drive independent technical investigation: survey relevant work, run experiments, form a clear point of view, and communicate findings clearly.
Strong product sense and care for UX and AX: tools should be intuitive for developers and ergonomic for agents.
A focus on real-world impact: we want research to become enterprise capabilities, reference implementations, developer workflows, or product improvements.
Outstanding team orientation and comfort collaborating across research, engineering, product, design, solutions, and developer-facing teams.
Ways to stand out from the crowd:
Experience with secure agent runtimes, tool sandboxing, capability-based security, or enterprise policy systems.
Experience with compliance or enterprise governance requirements such as auditability, data retention, access control, SOC2, HIPAA, GDPR, or regulated deployment environments.
Experience with LLM inference infrastructure, model serving, or inference optimization using tools such as Triton, TensorRT-LLM, vLLM, SGLang, Ray, Kubernetes, or cloud GPU platforms.
Experience integrating inference backends into agentic systems, including routing across models, tool-aware context management, streaming, structured outputs, retries, monitoring, and cost/performance optimization.
Experience developing or maintaining open-source software in AI agents, LLM systems, developer tooling, ML infrastructure, model serving, or related areas.
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 on the planet working for us. If you're creative, passionate and self-motivated, we want to hear from you! NVIDIA is leading the way in groundbreaking developments in Artificial Intelligence, High-Performance Computing and Visualization. The GPU, our invention, serves as the visual cortex of modern computers and is at the heart of our products and services.
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
Software Engineer, OpenShell at NVIDIA rates 98 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
- $184k
- Typical software engineer job
- $168k
This posting starts 10% above the typical software engineer job. See software engineer jobs
Questions you could be asked
- How do you decide when an AI agent can act on its own versus asking for approval first?
- Tell me about a research question you investigated. What did you find?
- What are the limits of vLLM that you've run into, and how did you work around them?
- How would you decide a model or AI system is ready to ship?
- Tell me about a time a model underperformed in production. How did you find out, and what did you change?
Adapt your resume
- List these exact terms on your resume: AI agents, AI Research, 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.
- 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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