We are an applied AI lab building end-to-end software agents.

We're the makers of Devin, the first AI software engineer.

Our team is extremely talent-dense. Among our founding team, we have world-class competitive programmers, former founders, and leaders from companies at the cutting edge of AI including Scale AI, Palantir, Cursor, Waymo, Tesla, Lunchclub, Modal, Google DeepMind, and Nuro.

Building Devin is just the first step—our hardest challenges still lie ahead. If you’re excited to solve some of the world’s biggest problems and build AI that can reason on real-world tasks, apply to join us.

About the Role

Applied AI Engineers are how Cognition operationalizes AI modernization at the enterprise level. You don't demo Devin - you deploy it. You embed with engineering teams, integrate agentic workflows into how they actually build and ship, and drive the kind of measurable productivity gains that make adoption irreversible.

As one of our first Applied AI Engineers, you'll also shape the function itself - turning individual customer engagements into repeatable playbooks, digital learning content, and partner-driven enablement models that allow Cognition to reach hundreds of thousands of engineers worldwide.

This role is perfect for someone who has strong engineering fundamentals, enjoys working directly with customers, and finds deep satisfaction in driving product adoption and having users unlock their potential with Devin - while also thinking systematically about how to scale those learnings to the next 100 teams.

In this role, you will:

• Embed with enterprise engineering teams to drive deep, lasting adoption of Devin — owning outcomes, not just onboarding
• Architect and implement agentic workflows across engineering, QA, support, data, and product — identifying where AI creates the highest leverage and building toward it
• Lead interactive programs for enterprise engineering teams (live workshops, pair programming sessions)
• Guide customers through installing, configuring, and optimizing Devin and its associated tools (DeepWiki, MCP integrations, etc.)
• Pair-program on live production problems to demonstrate high-value usage patterns and accelerate the team's applied AI fluency
• Quantify impact — tracking productivity metrics, surfacing ROI stories, and making the business case for expanding Devin's footprint within accounts
• Work with leadership to scale field learnings into structured playbooks and best practices that scale beyond individual engagements
• Create enablement materials, best practices, and shared playbooks based on customer learnings