Replication Package: A Landscape of Agentic AI Engineering — An Empirical Analysis of Job Postings

This replication package contains all data, coding artifacts, inter-rater reliability assessments, and statistical analyses for reproducing the study findings. The study analyses 210 agentic AI job postings collected from four platforms (Glassdoor, LinkedIn, SimplyHired, Indeed) across 11 countries using Socio-Technical Grounded Theory for Data Analysis (STGT4DA). Contents:- Raw data from all 4 platforms (3,009 postings)- Final analysis corpus (210 postings) with full descriptions and metadata- Complete codebook with raw-to-canonical code mappings- Taxonomies: 34 responsibility codes, 45 hard skill codes, 18 soft skill subcategories- Binary matrices (responsibility × job, hard skill × job, soft skill × job)- Inter-rater reliability: coding phase (κ = 0.76, 30 postings, 718 statements) and filtering phase (κ = 0.763, 60 postings)- Second coder data with all agreements and disagreement resolutions- Co-occurrence analysis: Mann-Whitney U tests with Benjamini-Hochberg FDR correction for all 44 hard skills Full author details will be disclosed upon acceptance.