Software Engineer

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.

- 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.

- 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.

- Base Salary: $260,000 - $300,000 + Significant early-stage equity

- Perks: Private chef, cozy slippers, endless snacks, and more