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Oriana Rodriguez

Senior Technical Recruiter

Global TA — Robotics & AI

Robotics/Embedded Recruiter

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Oriana Rodriguez

Senior Technical Recruiter

Global TA — Robotics & AI

Robotics/Embedded Recruiter

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Transferring Tech Recruiting Heuristics to Creative Engineering Domains: A Hybrid Skill Taxonomy Model for Sourcing Top-Tier Designers and Developers

This paper is part of the International Journal of Applied Research in Business and Management (ISSN: 2700-8983), Volume 6, Issue 2, published in 2025.

All IJARBM articles are:

  • Peer-reviewed (rigorous, timely, constructive).

  • Open Access under CC BY 3.0.

  • Indexed in Crossref, DOAJ, EBSCO, EconBiz, Google Scholar, ResearchGate, Semantic Scholar.

  • Assigned a DOI and listed in the German National Library systems (ZDB, German National Bibliography) and the ISSN Portal.

Badges: Crossref · DOAJ · Open Access · DOI · Google Scholar · EBSCO · EconBiz · Semantic Scholar · ResearchGate

Authors

Oriana Valentina Rodríguez Guedes

Abstract

Few candidates will ever squeeze their elite designers and developers into conventional recruitment funnels; non-technical recruiters are especially found wanting in sourcing for creative engineering specialities. Herein, we present a hybrid skills framework enhanced by AI tools that enable recruiters to make confident hiring decisions without requiring in-depth domain knowledge. By merging algorithmic evaluation of candidate work products from GitHub, Figma, and Behance with natural language processing of voice-interview transcripts, our approach converts a subjective experience into a reproducible process driven by objective metrics. At its core lies the SNRHiring Index, a proprietary composite score computed from hard skills and behavioural stimuli verified against real-world digital signals. Built with scalability and transparency in mind, this framework has since been applied in a production setting for tech recruitment, reducing hiring time, increasing the quality-to-fit rate of portfolios, and improving post-hire retention. The conclusions, therefore, enable the building of a repeatable playbook for HR practitioners, startup CTOs, and HRTech researchers interested in innovating creative technical hiring. By affording clients the ability to source high-quality talent even without insider knowledge, this paper thus contributes not only to the AI-hiring literature but also to establishing a DOI-citable proof of method for platform credibility, investor assurance, and transparency to clients.

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Suggested Citation (APA 7th)

Rodríguez Guedes, O. (2025). Transferring Tech Recruiting Heuristics to Creative Engineering Domains: A Hybrid Skill Taxonomy Model for Sourcing Top-Tier Designers and Developers. International Journal of Applied Research in Business and Management, 6(2). https://doi.org/10.51137/wrp.ijarbm.2025.ortf.45873

Published by Wohllebe & Ross Publishing in Germany.

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