
AI Process Architect
1 week ago
Job Summary
This is an exciting opportunity for a technical leader to architect, implement and scale AI-driven process automation, intelligent workflow mining and task orchestration.
The successful candidate will drive enterprise-grade AI platform development, ensuring seamless integration of structured (SQL) and unstructured data (images, videos, logs etc.) while leveraging Large Language Models (LLMs), Process Mining, Robotic Process Automation (RPA), Data Science and AI/ML techniques for automation, scalability and decision intelligence.
Key Responsibilities:
- Architectural Design:
- Develop 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 Generalized AI (GenAI), RPA and Intelligent Process Automation.
- Mentor teams on AutoGen-based AI workflow orchestration and scalable AI agent development.
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