Part 2 of our guide to build an AI Agent for Talent Matching using LLMs to match developers with job positions based on skills, experience, and nuanced context.

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Building an AI-powered talent matching system using LLMs to match developers with job positions requires careful prompt engineering and context management. The system uses a Ruby on Rails application with the Active Genie gem to score candidates against job requirements. Developer profiles are converted from survey data into structured text prompts, while job positions are formatted with responsibilities and requirements. Claude 4.5 Sonnet was chosen for its ability to understand implicit context and nuance beyond simple keyword matching. The system generates scores for all developers and presents the top 5 candidates with AI reasoning to the commercial team for final decision-making. Future improvements include building an AI-powered resume parser to enhance the dataset with career history information.

How To Build An AI Agent For Talent Matching – Part 2