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Ashby Verified ATS

Software Engineer, Plugin Ecosystem

Openai San Francisco 1mo ago
FullTime
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About Openai (Wikipedia Record):

OpenAI is an American artificial intelligence (AI) public benefit corporation (PBC) headquartered in San Francisco, California. It develops "frontier" generative AI models, particularly its generative pre-trained transformer (GPT) series of large language models.

About the Role

About the Team The Plugin Ecosystem team builds the platform and product experiences that let people extend ChatGPT and Codex. We work on plugins, skills, connectors, interactive apps, and open standards like the Model Context Protocol (MCP). We make plugins easy to discover, install, and use, ensure they’re invoked at the right time, and help people find new ways to get value from them. We want anyone to be able to turn a useful workflow into a plugin, share it, and have other people use it. A plugin can package instructions and skills with connections to the tools and data it needs. Our work spans creation and publishing, reliable execution across our products, clear permissions and approvals, and the controls admins need to bring plugins to their organizations. We work closely with research to improve plugin quality as models evolve. About the Role We’re looking for product-minded engineers to build the systems behind plugins and improve how models use them. Depending on your focus, you may scale generalist infrastructure and identity-related integrations across products, or improve plugin quality at the intersection of backend engineering and applied AI or work on the product experience itself to drive plugin usage. You’ll work across teams and own problems from diagnosis and design through implementation and release. This role is based in San Francisco. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: - Design and ship APIs, SDKs, and services that developers use to extend ChatGPT and Codex. - Build intuitive experiences that help users discover, install, and use plugins to get more done. - Make plugins easier to create, test, publish, update, and share. - Improve when and how models use plugins, from choosing the right plugin to completing a task. Work with Research to diagnose failures and measure improvements as models evolve. - Improve plugin reliability and

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