Software Engineer, OpenShell

Overview

Research engineer role on NVIDIA's OpenShell team, building runtime infrastructure for secure, scalable, production-grade AI agents. The role bridges research, product, and engineering to turn agentic-systems advances into enterprise capabilities.

What you'll do

• Track the cutting edge of agentic systems, including tool use, planning, memory, evaluation, self-improvement, multi-agent workflows, runtime infrastructure, and agent safety/security.
• Identify research ideas that can meaningfully improve OpenShell and translate them into concrete product opportunities.
• Reproduce and test promising methods from papers, open-source projects, industry work, and internal NVIDIA research.
• Build rapid hands-on prototypes using OpenShell, including agent harnesses, evaluation loops, self-improving workflows, and runtime-native developer experiences.
• Design evaluation and red-team harnesses that measure agent reliability, usefulness, scalability, safety, security, and developer experience.
• Help design secure-by-default workflows for agents operating with tools, code, files, credentials, and enterprise systems.
• Collaborate 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.
• 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.
• Focus on real-world impact: research becoming 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.

Nice to have

• 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.

Details

• Location: US, Remote.
• Expected base salary range: 184,000 USD – 287,500 USD, determined by location, experience, and other objective job-related factors; eligible for equity and benefits.
• Applications accepted at least until November 3, 2026.
• This posting is for an existing vacancy.