Human Capital Intelligence Agent, Corporate, Group 42 (G42)

Enterprise AI Agent Deployment
United Arab Emirates, Abu Dhabi
March 31, 2026
Full Time

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Job Description

The Human Capital Intelligence Agent at Group 42 (G42) operates as an AI system which provides production-ready capabilities to organizations for improving their workforce analytics and human resources operations. Developers must submit deployed AI agents which can operate with HR systems to provide workforce insights and automate processes while supporting secure enterprise infrastructure and operational performance metrics of responsible AI practices.

Job ID: 2705

Date Posted: NA

Expiration Date: NA

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Main Duties

  • Analyze workforce data to generate insights for talent acquisition, performance analytics, and organizational planning.
  • Integrate with enterprise HR systems such as HRIS, ATS, payroll, and workforce analytics platforms.
  • Automate human capital processes including talent management, employer branding analytics, and lifecycle management.
  • Provide explainable analytics, audit traceability, and decision support for HR leadership.
  • Maintain secure AI deployment with responsible AI practices, data protection, and enterprise compliance controls.

Essential Qualifications

  • The AI agent which has been deployed for production uses enterprise environments to conduct its operations. 
  • Technical architecture documentation includes components such as LLM framework and system design together with operational boundaries. 
  • Analyze structured workforce data to generate analytics reports which support enterprise HR operations. 
  • Architecture functions across all cloud platforms while supporting Azure-based enterprise operations. 
  • Operational transparency through its complete explanation capabilities together with audit trails and structured escalation processes.

Preferred Qualifications

  • The system showed successful linkage with HRIS, ATS and payroll systems and workforce analytics tools through its actual implementation at large organizations. 
  • AI agents produced documented productivity enhancements and measurable time savings which the user was able to verify. 
  • Develop performance benchmarks which measured system latency and reliability and operational capacity under enterprise working conditions. 
  • Responsible AI documentation which included bias testing results and bias mitigation methods and compliance management procedures. 
  • Demonstrated complete lifecycle development through its documented version updates and maintenance procedures and its connections to enterprise systems.