Forward Deployment Engineer - Devin/Claude AI with Java Experience

Introduction:

The Forward Deployment Engineers (FDEs) will act as hands-on full-stack engineers responsible for enabling and scaling GenAI tools (Devin, Claude Code, Cursor). They will lead the end-to-end rollout of these tools across CDXO and LOB engineering teams.

Responsibilities:

• Lead end-to-end rollout of Devin, Claude Code, and Cursor across CDXO and LOB engineering teams
• Act as hands-on full-stack developers, building and integrating solutions into enterprise SDLC workflows (CI/CD, repos, APIs)
• Define and execute enterprise rollout strategies, including phased onboarding and scaling models
• Partner closely with client teams to improve the overall product delivery lifecycle through effective and optimized utilization of GenAI tools
• Conduct developer onboarding, training, and enablement sessions, driving best practices for prompt engineering and workflow integration
• Monitor tool usage, performance, and efficiency metrics, and continuously optimize adoption and outcomes
• Provide hands-on troubleshooting, performance tuning, and scaling support for engineering teams
• Establish and promote best practices and reusable playbooks for enterprise-wide GenAI adoption
• Ensure alignment with client governance, security, and compliance requirements

Requirements:

• Successful deployment and scaling of Devin, Claude Code, and Cursor across CDXO and LOB teams
• Demonstrable improvement in the product delivery lifecycle, including faster development, testing, and remediation cycles through effective GenAI utilization
• Increased developer productivity and automation outcomes driven by optimized usage of Devin, Claude Code, and Cursor
• Defined, adopted, and standardized enterprise playbooks and best practices for GenAI usage across teams
• Continuous monitoring and reporting of adoption metrics, usage efficiency, and value realization
• Stable, secure, and governed integration of GenAI tools into the enterprise SDLC ecosystem
• Proactive identification and resolution of adoption gaps, inefficiencies, and scaling challenges