• 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