About the role
Who We Are Cognition is an applied AI lab building end-to-end software agents. We are behind Devin, the first AI software engineer, and Windsurf, an AI-native IDE. Our vision is AI that works alongside engineers as a genuine teammate, not a tool. We are a small, talent-dense team of competitive programmers, former founders, and researchers from Scale AI, Palantir, Cursor, Google DeepMind, and others. Role Mission Software Engineers at Cognition are not feature builders. You will be working on some of the hardest open problems in applied AI: how do you build an agent that can reason across thousands of lines of code, spawn and coordinate subagents, use tools reliably across ambiguous long-horizon tasks, and do all of this in a way that a real engineer would trust? You will ship systems that go directly into Devin and Windsurf, two products that millions of developers use to write, debug, and ship code. This is a role for engineers who want to be close to the frontier, who can move fast without cutting corners, and who believe the next 5 years of software engineering will look fundamentally different from the last 5. What You'll Accomplish Build core agent infrastructure: Design and ship the systems that power Devin's long-horizon task execution: tool use, context management, multi-step planning, subagent orchestration, and sandboxed code execution environments. Improve Windsurf as an AI-native IDE: Contribute to editor intelligence, agent-in-the-loop workflows, real-time code understanding, and the developer experience that makes Windsurf different from every other IDE. Close the loop between models and products: Work directly with researchers to translate new model capabilities into shipped features; your feedback shapes what gets prioritized in training. Own reliability and performance at scale: Build systems that handle millions of agentic tasks with low latency, high reliability, and the kind of correctness that developers depend on in production. Move the category forward: Cognition is defining what AI software engineering looks like. You will have real input into what gets built next and why. Exceptional Candidates Have Demonstrated Systems engineering depth: Experience building reliable, performant distributed systems; you have strong opinions about correctness, failure modes, and production behavior. Product instinct: You care about how the software you build feels to use and you have shipped things that real people depend on. Comfort with ambiguity: You can make progress on hard problems with incomplete specs, learn fast from results, and course-correct without needing a lot of direction. Velocity without shortcuts: A track record of shipping quickly while maintaining the kind of code quality that a high-density team expects. Curiosity about agents and AI: You have dug into how LLMs work, how agents fail, and what it takes to make AI-powered systems behave reliably in the real world. Strong Python proficiency: Python is the primary language across Cognition's codebase; you write clean, well-structured Python and are comfortable owning large Python codebases in production. Relevant industry experience: Prior experience at a frontier AI lab, applied AI company, or developer tools company; you know what good looks like in this category. Degree from a top-tier university: BS, MS, or equivalent in Computer Science, Mathematics, Engineering, or a related technical discipline from a highly selective program.