<ul><li>Candidates in the talent market are now being assessed for stack readiness in AI roles, which includes a combination of tools, applied skills, and ability to deliver against production-level AI requirements.</li><li>Job descriptions across various AI role clusters demand specific skills and knowledge in platforms and practices, indicating the need for pairing tools and skills in the industry.</li><li>Key skills and practices, as well as common tools and platforms, are highlighted for different AI role clusters such as Gen AI engineering, data engineering, AI/ML engineering, and Cloud AI engineering.</li><li>Skills like prompt engineering and retrieval-augmented generation (RAG) are increasingly important in AI roles, reflecting the convergence of user-facing and infrastructure-facing capabilities in the industry.</li></ul>

Stack readiness is what is sought in talent today: Report

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