AI Context Engineering Consultant

JOB SUMMARY

The Consultant - AI Context Engineering & Knowledge Enablement is a strategic consulting role focused on enhancing how enterprise AI development teams create, manage, and scale reusable context assets within AI-assisted development ecosystems. This role aims to boost developer productivity by optimizing context repositories, reusable skills, plugins, and shared knowledge assets, thereby improving the effectiveness of AI tools. By integrating technical enablement, repository governance, and consulting expertise, this position supports the enterprise-wide adoption of scalable context engineering practices essential for sustainable AI development success. Key Responsibilities

• Review and improve user-generated context assets, prompts, plugins, and reusable technical artifacts across enterprise AI repositories.
• Enhance the structure, quality, and reusability of context repositories to improve AI developer productivity.
• Develop and maintain reusable skills, templates, plugins, and context sources across enterprise and team environments.
• Create documentation, examples, and governance guidance to support sustainable context contribution and adoption.
• Partner with developers and stakeholders to refine context engineering practices and explore new enablement strategies. Required Qualifications
• 4+ years of experience with AI-assisted development tools, developer productivity, platform engineering, or related technical consulting roles.
• Experience reviewing, authoring, or curating reusable technical assets, repositories, or shared engineering resources.
• Strong understanding of Git-based collaboration, repository hygiene, and software development workflows.
• Proven ability to assess and improve content structure, quality, naming conventions, and reusability across technical teams.
• Strong documentation, technical writing, and knowledge management skills.
• Experience collaborating with developers to implement practical tooling and workflow improvements.
• Bachelor's degree in Computer Science, Engineering, Information Systems, Knowledge Management, or related field. Preferred Qualifications
• Experience with prompts, plugins, templates, reusable AI assets, or context engineering frameworks.
• Exposure to enterprise knowledge systems, metadata structures, or taxonomy management.
• Prior consulting or professional services experience.
• Experience driving enterprise adoption of shared developer tools or reusable engineering assets.
• Familiarity with AI governance, developer enablement, or enterprise transformation initiatives.