• develop a deep, shared understanding with NVIDIA's early-adopter engineering teams • identify the friction points where agentic workflows would have the highest impact • iterate with teams on proof points to validate or revise plans together • use technical judgment to distinguish durable architectural opportunities from "tech du jour" hype • agent-ify compiler infrastructure to enable autonomous agents to make high-dimensional optimizations • closed-loop validation on real hardware • integrate systems into git-native workflows and CI pipelines • contribute to cross-org collaborative group sharing reusable agentic methodology

• Design, build, test, and operate scalable data pipelines • Develop and maintain analytics-ready and AI-ready datasets • Contribute to technical designs for data-intensive systems • Implement production-quality code and infrastructure changes • Improve the quality, reliability, and scalability of data products • Collaborate with product owners, engineering managers, architects, and peer engineers • Improve team engineering standards and practices • Mentor less-experienced engineers

• Lead the design and architecture of major systems and services • Collaborate with solution managers, engineers, data scientists, and other stakeholders • Demonstrate experience delivering production software through agentic AI tooling • Understands the AI harness is engineered infrastructure • Collaborate with teams to ensure sustained quality and reliability of software solutions • Actively contribute to code reviews and provide constructive feedback • Drive innovation by evaluating and implementing new technologies • Ensure code meets functional and performance requirements • Leverage AI tools and platforms as an integral part of daily responsibilities

• Build and manage our best-in-class proxy tier servicing billions of HTTP requests per day. • Manage our global CDN platform that ships assets to clients’ browsers efficiently. • Work collaboratively with a niche team of experienced engineers. • Ship code to production and improve the experience of millions of Zendesk users. • Be a second set of eyes for your peers' code, changes and deployment plans. • Use a best-in-class modern technology stack: AWS, Cloudflare, Kubernetes, Terraform, Go, etc. • Use DevOps best practices: we build it, we run it.