AI Platform Engineering Lead

4 days ago

Chennai, Tamil Nadu, India beBeeAutomation Full time ₹ 1,60,00,000 - ₹ 2,01,00,000
AI Architect Job Description

This role is designed for a technical leader who will drive the development of AI-driven process automation, intelligent workflow mining, and task orchestration using AutoGen, CrewAI, WrenAI, and Azure AI.

The architect will lead the creation of an enterprise-grade AI platform that integrates structured (SQL) and unstructured data (images, videos, logs, etc.) while leveraging LLMs, process mining, RPA, Data Science, and AI/ML techniques for automation, scalability, and decision intelligence.

Responsibilities:

  • Architectural Design:
    • Define AI-powered process automation blueprints and agentic AI frameworks.
    • Design scalable, secure, and high-performance architectures for AI-first process mining and discovery.
    • Establish LLM-based active learning pipelines for continuous improvement and adaptability.
  • Implementation and Development:
    • Lead the development of AI-driven workflow automation using AutoGen's inter-agent collaboration.
    • Build process intelligence layers to optimize execution, anomaly detection, and decision automation.
    • Develop and deploy RPA-enhanced AI agents for business process transformation.
  • Integration and Testing:
    • Integrate Azure AI Search, Vector DBs, and Intelligent Process Automation to extract insights from enterprise data.
    • Implement multi-modal AI pipelines handling structured and unstructured inputs for dynamic processing.
    • Optimize AI-driven anomaly detection for automated error resolution and predictive analytics.
  • Optimization and Performance Tuning:
    • Leverage ML-driven process mining for automated workflow discovery, execution efficiency, and intelligent recommendations.
    • Implement continuous AI learning cycles to improve accuracy and execution speed over time.
    • Optimize end-to-end process intelligence dashboards using advanced NLP and BI visualizations.
  • Documentation and Knowledge Sharing:
    • Develop comprehensive architectural documentation for AI-driven process intelligence solutions.
    • Lead knowledge-sharing initiatives to align teams on best practices in GenAI, RPA, and Intelligent Process Automation.
    • Mentor teams on AutoGen-based AI workflow orchestration and scalable AI agent development.

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