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Forward Deployment Engineer - Devin/Claude AI with Java Experience

Contract
Posted 3 weeks ago
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Where you can work

Remote

Open to candidates in United States

Locations named in the listing

  • Charlotte, North Carolina, United States
View location wording from the posting
  • Charlotte, NC, US
  • Remote - US

Employer description

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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