About Us

At Cloudflare, we are on a mission to help build a better Internet. Today the company runs one of the world’s largest networks that powers millions of websites and other Internet properties for customers ranging from individual bloggers to SMBs to Fortune 500 companies. Cloudflare protects and accelerates any Internet application online without adding hardware, installing software, or changing a line of code. Internet properties powered by Cloudflare all have web traffic routed through its intelligent global network, which gets smarter with every request. As a result, they see significant improvement in performance and a decrease in spam and other attacks. Cloudflare was named to Entrepreneur Magazine’s Top Company Cultures list and ranked among the World’s Most Innovative Companies by Fast Company.

At Cloudflare, we’re not looking for people who wait for a polished roadmap; we’re looking for the builders who see the cracks in the Internet that everyone else has simply learned to live with. We value candidates who have the instinct to spot a "normalized" problem and the AI-native curiosity to create a solution using the latest tools. Our culture is built on iteration, leveraging AI to ship faster today to make it better tomorrow, while ensuring that every improvement, no matter how small, is shared across the team to lift everyone up. If you’re the type of person who values curiosity over bureaucracy, and that AI is a partner in solving tough problems to keep the Internet moving forward, you’ll fit right in.

Available Locations: Austin, TX | Lisbon, Portugal | London, UK

About the role

The Snr Software Engineer, AI & Infrastructure Planning role helps Cloudflare build, deploy, and operate one of the world's largest distributed networks. You will build an auditable multi-agent system on Cloudflare’s platform to replace notebooks and email threads with agent-driven forecasts, supply plans, cost models, and workflow approvals into agent workflows that planners & executives rely on for decision analysis.

Responsibilities

Collaborate closely with capacity planning, networking, and data center engineering teams to encode technical domain expertise into structured specifications, formal data contracts, and agent functional capabilities.
Architect, deploy, and maintain scalable production agents and durable workflows leveraging the Cloudflare Workers ecosystem, including Durable Objects, Workflows, D1, R2, Queues, Vectorize, Workers AI, and AI Gateway.
Translate core infrastructure planning functions—such as forecasting, supply planning, cost modeling, narrative documentation, and executive approvals—into automated LLM deployment or deterministic logic based agent workflows designed for critical decision-making analysis.
Implement rigorous risk tiering, formal approval checkpoints, detailed audit logs, and execution lineage to ensure safe autonomous operations.
Incorporate predictive statistical and machine learning models into agent systems, establishing robust BigQuery data pipelines, optimized access patterns, and continuous monitoring.
Author comprehensive technical specifications and Requests for Comments (RFCs), perform peer design reviews, and establish architectural standards for AI agent deployment across the organization.

Desirable Skills, Knowledge, and Experience

Senior-level software engineering experience, with security conscious production systems you can point to (repos, releases, services you operated).
Strong TypeScript, and comfort building on serverless or edge runtimes (Cloudflare Workers preferred). HTTP APIs, async, queues, performance.
Experience with LLMs and agents: tool calling, structured output, multi-step or multi-agent orchestration, prompt and eval iteration.
Experience with durable state and workflows (Durable Objects, Cloudflare Workflows, or equivalents such as Templets updraoral or Step Functions).
Demonstrated experience in infrastructure planning: capacity planning, forecasting, networking, CDN, cloud or data center capacity, or adjacent work. We will teach you our specific systems.