À propos de ce poste Staff Backend Engineer- Agent Experience (AX) chez Cloudinary
Cloudinary is the media experience platform trusted by millions of developers and thousands of companies — from fast-growing startups to the world's largest brands — to power the images and video behind their digital experiences.
Something fundamental is changing about who uses that platform. Increasingly, the "developer" calling our APIs isn't a person — it's an agent: an LLM, a coding assistant, an autonomous pipeline acting on a human's behalf.
Our Agent Experience (AX) R&D team exists to make Cloudinary the default media layer those agents run on. Our guiding principle is simple: make agentic workflows work flawlessly with no friction.
We're a small, fast, high-ownership team, and we're looking for a Senior Backend Engineer to make Cloudinary work for agents — both by building new agent-facing infrastructure and by reshaping our existing platform for a world where the caller is a machine. Some of this is greenfield. Much of it is taking APIs, auth, and SDKs and making them ergonomic, legible, and reliable for agents.
It’s a problem the whole industry is still figuring out. You’ll help define what great API design looks like when the caller is not a human developer, but an agent acting on their behalf.
What you'll do
About you
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10+ years building and operating production APIs, SDKs and Backend systems and at scale.
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Strong in Node.js/TypeScript, and comfortable working in (or quickly ramping on) Ruby/Rails and/or Go.
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Deep API and protocol design fundamentals — authentication (OAuth, API keys, scoped permissions), versioning, idempotency, rate limiting, clean contracts.
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Genuine curiosity about agents and LLMs and how they're reshaping how software gets built and run.
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Solid distributed-systems and cloud instincts (AWS or equivalent).
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A bias for ownership in ambiguity — you scope the problem, not just the solution, and you ship.
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Strong written communication — it matters more than usual when your consumers are machines and your teammates are distributed.
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Hands-on experience with MCP, LLM tool/function-calling, or building AI-/agent-native products.
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Experience building SDKs, CLIs, or developer tools that other engineers depend on.
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Background in media, imaging, or video processing/delivery.
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Open-source contributions in the agent or developer-tooling ecosystem.
