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Forward Deployment Engineer - Devin​/Claude AI Java

Job in Charlotte, Mecklenburg County, North Carolina, 28245, USA
Listing for: Delan Associates, Inc
Full Time position
Listed on 2026-10-11
Job specializations:
  • Software Development
    Full Stack Developer, AI Engineer (Applied/Software), DevOps
Salary/Wage Range or Industry Benchmark: 140000 - 210000 USD Yearly USD 140000.00 210000.00 YEAR
Job Description & How to Apply Below
Job Description:

The Forward Deployment Engineers (FDEs) will act as hands‑on full‑stack engineers responsible for enabling and scaling GenAI tools (Devin, Claude Code, Cursor).

The

Role 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
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