4 days ago
Base Salary
$168k - $270k/yr
Responsibilities
- Design and implement agentic AI workflows using LLM-based agents, tool calling, RAG patterns, and orchestration frameworks.
- Build automation pipelines and integrations across ServiceNow, identity management, monitoring platforms, and enterprise SaaS.
- Own full-stack systems spanning infrastructure and user-facing tools.
- Triage and resolve enterprise issues while improving mitigation and resolution times through automation.
- Manage and troubleshoot enterprise-scale collaboration, productivity, AI, and infrastructure systems.
- Trace complex multi-system failures, identify recurring issue patterns, and build automation or self-service solutions.
- Create and maintain runbooks, troubleshooting guides, and knowledge base articles.
- Mentor team members in troubleshooting methodology and systems thinking.
Requirements
- Bachelor's degree or equivalent experience.
- At least 8 years of experience in SRE, enterprise support, or DevOps.
- Experience with SaaS, hybrid cloud, and AI/ML environments.
- Experience building production-grade agentic workflows, including multi-agent systems and MCP servers.
- Deep software engineering experience building products and operating large-scale systems.
Benefits
- Equity and benefits are provided.
- The expected base salary is determined by location, experience, and other objective job-related factors.
- Applications will be accepted at least until November 6, 2026.
Categories
About Nvidia
Nvidia designs and sells GPUs and accelerated computing platforms for data centers, AI/ML, graphics, gaming, and automotive, monetizing through hardware, software platforms (CUDA, AI frameworks), and systems like DGX and networking. Customers include cloud providers, enterprises, researchers, and OEMs. Founded in 1993 and headquartered in Santa Clara, it is a public company traded on NASDAQ under NVDA.