Job Title : GitHub Copilot Adoption Framework GCAF Collaborative Engineer

Location : Remote

Job Type : Full-Time

About the Company :

Amtex Systems Inc is a global technology solutions provider specializing in digital transformation, AI-driven innovation, cloud solutions, data engineering, and enterprise consulting. With decades of industry experience, Amtex helps organizations accelerate growth through cutting-edge technologies, engineering excellence, and a strong culture of innovation.

About the Role :

We are seeking a highly experienced GitHub Copilot Adoption Framework GCAF Collaborative Engineer to lead AI-driven software development adoption across distributed engineering teams. This role requires deep expertise in GitHub Copilot, Amazon Q, prompt engineering, modern coding practices, and AI-assisted developer productivity tools. The position is fully remote and involves close collaboration with engineering, DevOps, cloud, and product teams.

Key Responsibilities :

AI Copilot Engineering and Automation :

- Design, develop, and optimize coding workflows using GitHub Copilot and Amazon Q Developer tools.

- Work with advanced features such as Copilot Chat agents and Amazon Qs dev command.

- Implement AI-based coding assistance for complex development tasks.

Prompt Engineering and Knowledge Modeling :

- Create advanced prompts and structured instructions to maximize AI productivity.

- Develop prompt frameworks and reusable patterns for engineering teams.

- Collaborate with teams to curate internal datasets that enhance AI knowledge and reasoning.

Copilot Enterprise and Amazon Q for Business Enablement :

- Configure, implement, and optimize Copilot Enterprise and Amazon Q for Business.

- Support RAG-based architectures, internal codebase indexing, and secure AI usage.

- Ensure AI copilots follow governance, compliance, and security requirements.

Developer Productivity and Workflow Integration :

- Integrate AI copilots into engineering practices such as GitHub Flow, Agile methodology, and version control workflows.

- Develop automation scripts, templates, and custom actions to improve development speed and quality.

- Train development teams on AI-assisted coding workflows and best practices.

Cloud, DevOps, and Tooling Collaboration :

- Work with Cloud and DevOps teams to integrate AI into workflows involving AWS, IaC, and CI CD.

- Enhance pipelines, code reviews, testing, and documentation using AI techniques.

- Recommend improvements to modernize engineering tools and practices.

Required Skills and Qualifications :

- Minimum 1 to 3 years of professional software engineering or DevOps experience.

- Expert-level knowledge of GitHub Copilot and Amazon Q, including real-world enterprise usage.

- Hands-on experience with Copilot Chat agents, Amazon Q dev command, Copilot Enterprise, and Amazon Q for Business.

- Advanced prompt engineering capabilities for both GitHub and Amazon AI ecosystems.

- Intermediate understanding of LLM fundamentals, AI security, AI ethics, retrieval mechanisms, and reasoning techniques.

- Advanced proficiency in at least one programming language such as Python, JavaScript or TypeScript, or Java.

- Expert-level proficiency with IDEs such as VS Code and JetBrains tools.

- Strong understanding of GitHub Flow, branching strategies, code reviews, and Agile SDLC.

- Intermediate knowledge of AWS, Infrastructure as Code, and CI CD concepts.

Preferred Qualifications :

- Experience in implementing AI copilots or developer productivity frameworks across enterprises.

- Familiarity with MLOps, embeddings, vector databases, or AI workflow orchestration.

- Experience conducting workshops or training sessions for engineering team enablement.

- GitHub or AWS certifications are an added advantage.

What This Role Offers :

- Opportunity to lead AI engineering adoption across global teams.

- Exposure to cutting-edge AI tools and modern development practices.

- Fully remote role with strong collaboration across diverse technical teams.

- Opportunities for career advancement in AI-driven engineering and cloud-native ecosystems.