Senior Software Engineer, Core Frameworks & Protocols (Open-Source)

About Us CopilotKit is the #1 open-source platform for building AI Copilots — intelligent agents designed to work with users inside of real applications. In our first two years, we’ve delivered the fastest growing Javascript AI framework of all time, and built a vibrant community (40k+ GitHub stars, millions of weekly installs, 10s of millions of copilot interactions, double-digit MoM growth), are already monetizing at the enterprise level, and are used by companies ranging from startups to Fortune 100s (including production usage by over 10% of Fortune 500s). We’re emerging as the default for a critical part of the AI stack: the agent/user interaction layer. CopilotKit brings agents out of demos and terminals and into production, through deep integrations with the leading AI infrastructure companies and hyper-scalers (including the leading AI/infra teams at Google, Microsoft, Amazon, Oracle, LangChain, Mastra, Pydantic, Agno, and others). Our small, fast-moving team is building the agentic application platform that will define how user-interactive AI actually manifests in the real world. This is a unique opportunity to join as an early leader on one of the most complex and high-leverage surfaces in AI — with significant scope for technical, product, and leadership growth. The Role You'll build the core infrastructure powering the next generation of AI-native applications. This is a deeply technical role designing TypeScript & Python SDKs, real-time systems, and developer-facing abstractions used by tens of thousands of engineers. You'll work upstream of our headless UI layer, collaborating with leading AI infrastructure teams and hyperscalers to make integrating AI copilots seamless. You'll own systems end-to-end and help shape how production-grade AI agents interact with users. We're Looking for Pilots, Not Just Mechanics We need engineers who think at the level of systems and outcomes. You're fluent in AI-assisted development as your primary mode of working—directing AI to generate, refactor, and explore while evaluating outputs and course-correcting in real time. You've shipped meaningful work this way and understand that great developer infrastructure requires this higher-level perspective.