Senior Systems Engineer, AI Gateway
Cloudflare · In-Office
About this role
**Senior Systems Engineer, AI Gateway** **About Us** At Cloudflare, we’re on a mission to help build a better Internet. We protect and accelerate internet applications online—without adding hardware, installing software, or changing a line of code. Our intelligent global network routes traffic and gets smarter with every request, improving performance while decreasing spam and other attacks. We value builders who spot “normalized” problems and bring AI-native curiosity to create solutions with the latest tools. Our culture is built on iteration: leveraging AI to ship faster today to make it better tomorrow, and sharing improvements across the team. **Available Locations** Austin, TX or San Francisco, CA **About the Role** AI inference is becoming core infrastructure. Every serious application needs access to many models across many providers—with reliability, observability, security, cost control, and routing built in from the start. AI Gateway is Cloudflare’s bet that this layer should exist at the network edge: close to users, close to compute, and simple enough for developers to adopt with one API change. We’re looking for a **Senior Systems Engineer** to help build this layer. This is a deeply hands-on individual contributor role: move from half-formed product ideas to working, production-ready systems quickly. You’ll work across the stack—from distributed systems and high-throughput APIs to developer workflows, dashboards, SDKs, and docs—helping define how developers build and operate AI applications on Cloudflare. **Responsibilities** - Build core AI Gateway systems handling high-volume inference traffic across providers, models, and Cloudflare’s global network. - Design and implement APIs, routing primitives, observability features, controls, and developer workflows to make AI Gateway reliable and easy to adopt. - Collaborate across product and infrastructure boundaries with Workers AI, Agents, and the Developer Platform organization. - Turn ambiguous product and technical ideas into prototypes, design docs, shipped features, and measurable production improvements. - Improve reliability, performance, cost efficiency, and debuggability for latency-sensitive AI workloads. - Build “the software that builds the software”: agents, tests, harnesses, evaluation loops, operational tools, and internal context. - Sweat the developer experience (error messages, SDKs, dashboard flows, docs, examples, and API details). - Mentor engineers through design review, code review, debugging, and technical leadership. - Bring strong opinions and clear judgment, and revise your view when data, users, or production reality prove otherwise. **Desirable Skills, Knowledge & Experience** - 5+ years building and operating production systems (ideally AI infrastructure, developer platforms, cloud infrastructure, edge/proxy systems, high-scale APIs, or distributed systems). - Strong systems engineering fundamentals: networking, APIs, reliability, observability, data modeling, performance, and operational tradeoffs. - Experience designing/scaling distributed systems where latency, throughput, availability, and correctness matter. - Ability to work across the stack (API/product surfaces, backend services, queues, storage systems, control planes, performance-critical code). - Strong developer tools taste (APIs, SDKs, dashboards, CLIs, docs, internal platforms). - Clear technical communication (design docs, explaining tradeoffs, aligning engineers and produ
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