Role: Forward Deployment Engineer (FDE) – GenAI / Full Stack Architect Location : Charlotte NC Or Irving TX (Onsite) Rate : $80/hr. Indent : PSL-US213797_1-12-1
Roles & Responsibilities Hands-on full-stack engineers responsible for enabling and scaling GenAI tools (Claude Code, Cursor, OpenAI, Gemini) across Organization.
Lead end-to-end rollout of 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 different Line Of Business 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 Wells Fargo governance, security, and compliance requirements
Overview We are seeking highly skilled Forward Deployment Engineers with deep expertise in Devin/ ClaudeCode/CursorAI and modern GenAI tools to support enterprise-scale rollout and adoption across Wells Fargo. This is a hands-on full-stack engineering role focused on enabling LOB teams to improve the product delivery lifecycle through effective utilization of GenAI tools.
Key Responsibilities
Design, develop, and deploy GenAI-powered solutions using Devin, Claude Code, and Cursor
Integrate GenAI tools into enterprise SDLC workflows (CI/CD, internal platforms)
Partner closely with Wells Fargo LOB teams to accelerate delivery and improve the end-to-end product lifecycle using GenAI capabilities
Lead tool onboarding, training, and enablement, driving adoption and best practices across teams
Monitor and optimize tool usage, efficiency, and performance outcomes
Establish and drive best practices for GenAI usage, including prompt engineering and workflow integration
Provide hands-on troubleshooting, performance tuning, and scaling support