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# Developer / Trainer - AI Enablement Lead

- **Company:** CINTER CAREER USA, LLC
- **Location:** Plano, TX, United States
- **Experience:** Expert
- **Salary:** $104,000.0 - $124,800.0
- **Contract:** Temporary contract
- **Skills:** Application Programming Interfaces (APIs), Agile Methodology, Artificial Intelligence, Amazon Web Services, Cloud Computing, Code Review, Software Debugging, DevOps, Systems Development Life Cycle, Software Engineering, GitHub Copilot, Large Language Models, Prompt Engineering, Devsecops
- **Published:** August 3, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=9228132b33aee8b2

## About the Role

* Strong technical credibility with software engineering or solution architecture experience.
 * Excellent presentation, facilitation, and communication skills.
 * Ability to explain complex AI concepts to technical and non-technical audiences.
 * Hands-on approach to training through demos and practical exercises.
 * Passion for developer enablement and enterprise AI adoption.
 * Ability to balance innovation with responsible AI governance.

 * ︎ Required Qualifications & Skills:

 * Bachelor's degree or equivalent experience.
 * 5+ years of experience in software engineering, solution architecture, DevOps, platform engineering, developer relations, or technical enablement.
 * Hands-on experience with AI-assisted development tools and workflows.
 * Experience designing and delivering technical training.
 * Strong understanding of the SDLC.
 * Knowledge of responsible AI, security, privacy, and governance.
 * Preferred: GitHub Copilot, OpenAI Codex, Claude Code, AWS Kiro, prompt engineering, RAG, LLMs, APIs, cloud platforms, DevSecOps, Agile.

## Description

* Design and deliver hands-on AI training for software engineers, architects, and technical teams.
 * Develop AI curriculum, workshops, labs, demos, facilitator guides, and reusable learning materials.
 * Teach practical AI usage across the software development lifecycle, including coding, testing, debugging, documentation, and code review.
 * Facilitate live workshops, bootcamps, hackathons, and internal technical enablement sessions.
 * Collaborate with engineering, architecture, cybersecurity, cloud, data, and product teams.
 * Promote responsible, secure, and effective AI adoption across engineering teams.
 * Create prompt libraries, technical playbooks, reference examples, and reusable patterns.
 * Gather learner feedback and continuously improve training content.
 * Stay current with AI coding assistants, LLMs, agentic workflows, and enterprise AI best practices.
 * Advise on AI model selection, implementation strategy, and token/cost management.


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