Architect

Area(s) of responsibility

•    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.
2. 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.
3. 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.
4. 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.
5. 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.
Skills Required:
•    Must have: AutoGen Framework, CrewAI, WrenAI, Task Automation Agents, and Process Intelligence Systems.
•    Must have: Deep experience in AI-driven Process Discovery, Mining, and RPA Integration.
•    Must have: Azure AI Search, Vector DBs for process intelligence, and AI-powered workflow automation.
•    Must have: Hands-on expertise in SQL, unstructured data processing, and AI-based data curation pipelines.
•    12-14 years in AI platform engineering, process automation, and intelligent systems development.
•    5+ years recent leading AI-powered enterprise automation projects using Python, Flask/Django/FastAPI.
•    Expertise in building ML/AI pipelines leveraging Azure Synapse, AI Search, and LLM-based analytics.
•    Experience designing vector databases (Pinecone, FAISS, Weaviate, ChromaDB) and AI-powered workflow models.
•    Deep expertise in AI/ML-powered business process modeling for task orchestration and intelligent automation.
•    Knowledge of Azure Form Recognizer, OCR for intelligent document processing, and NLP-driven automation.
•    Hands-on experience with AutoGen, TaskWeaver, RAG, RLHF, and process-driven AI workflow automation.
•    Strong communication, architecture sketching, and AI-driven platform development expertise.