Gen AI Engineer
US client via staffing partner · Charlotte, NC
- Location
- Charlotte, NC
- Salary band
- Band not stated
- Type
- Contract
- Level
- Senior
- Work authorization
- Not stated
Stack
Devin AI · Claude Code · GitHub Copilot · CI/CD · Cloud-native applications · Agentic AI · GenAI · RAG · Prompt engineering · Context engineering · DevOps · Platform engineering · API development · Microservices · Workflow automation · Software testing · AI-assisted development
About the role
Job title: Gen AI Engineer Location: Charlotte, NC Duration: Long Term only W2 Key Responsibilities: Design, develop, test, and deploy software solutions in partnership with engineering teams. Leverage Devin AI and Claude Code to accelerate development, testing, debugging, documentation, and modernization initiatives. Create and maintain reusable AI artifacts including Devin Playbooks, Knowledge assets, CLAUDE.md files, Skills, and Hooks. Contribute to repository onboarding and AI workflow standardization efforts. Collaborate with architects, product owners, and engineers to deliver high-quality software solutions. Ensure AI-generated code meets engineering, security, quality, and compliance standards. Continuously evaluate and improve AI-assisted development workflows and engineering practices. Share best practices and lessons learned across development teams. Ideal Candidate: Strong software engineering and software delivery experience. Experience with modern development practices, CI/CD, testing, and cloud-native applications. Hands-on experience using AI coding tools such as Devin, Claude Code, GitHub Copilot, or similar platforms. Ability to effectively collaborate with AI agents to plan, build, test, and maintain software solutions. Strong problem-solving, communication, and teamwork skills. Passion for improving developer productivity through automation and AI-assisted engineering. Success Looks Like: Delivers software faster while maintaining high quality standards. Effectively leverages Devin and Claude Code as part of daily development activities. Creates reusable Playbooks, Knowledge assets, Skills, Hooks, and workflow templates that benefit multiple teams. Contributes to a growing catalog of AI engineering assets and best practices. Helps reduce development cycle times and improve engineering throughput. Demonstrates strong ownership, collaboration, and continuous improvement in AI-assisted software development. Nice-to-Have Skills: Agentic AI development GenAI application development RAG and workflow automation Prompt and context engineering DevOps and platform engineering experience API and microservices development
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