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Cognition AI is building Devin, the first AI software engineer, and is now scaling enterprise adoption of its agentic AI platform. As an Applied AI Engineer based in Singapore, you will be a key member of the team operationalizing AI modernization at the enterprise level.
You will embed directly with enterprise engineering teams to drive deep, lasting adoption of Devin and related tools (DeepWiki, MCP integrations). Rather than conducting demos, you will deploy the platform into production environments, integrate agentic workflows into how teams build and ship, and drive measurable productivity gains that make adoption irreversible.
Key responsibilities include: architecting and implementing agentic workflows across engineering, QA, support, data, and product functions; identifying where AI creates the highest leverage; leading interactive enablement programs (live workshops, pair programming sessions); guiding customers through installation, configuration, and optimization; pair-programming on live production problems to demonstrate high-value usage patterns; quantifying impact through productivity metrics and ROI storytelling; and scaling field learnings into repeatable playbooks and best practices.
As one of the first Applied AI Engineers, you will also shape the function itself—turning individual customer engagements into structured playbooks, digital learning content, and partner-driven enablement models that allow Cognition to reach hundreds of thousands of engineers worldwide.
You should have 3+ years as a software engineer, technical consultant, deployment strategist, forward deployed engineer, or solutions engineer with strong coding proficiency (Python, JavaScript/TypeScript, or similar). You must demonstrate proven ability to communicate complex technical topics to diverse audiences, drive technical adoption with measurable impact inside engineering organizations, and possess strong commercial instincts. Fast learning, adaptability, and excellent communication skills are essential.
Ideal candidates have led developer enablement or platform adoption initiatives with documented metrics, deployed LLM or agent-based systems in production, or joined early-stage startups where autonomy and execution speed were critical. You should be energized by seeing a team's velocity compound after working with them and engineer those outcomes deliberately.
About Cognition AI
AI / Data / Infrastructure — AI software engineering agents and developer automation.
