Gen AI Architect

About the Company

Birlasoft, a global leader at the forefront of Cloud, AI, and Digital technologies, seamlessly blends domain expertise with enterprise solutions. The companys consultative and design-thinking approach empowers societies worldwide, enhancing the efficiency and productivity of businesses. As part of the multibillion-dollar diversified CKA Birla Group, Birlasoft with its 12,000+ professionals, is committed to continuing the Groups 170-year heritage of building sustainable communities.

About the Role:

This role is designed for a technical leader who will architect, implement, and scale AI-driven process automation, intelligent workflow mining, and task orchestration using AutoGen, CrewAI, WrenAI, and Azure AI. The architect will drive enterprise-grade AI platform development, ensuring seamless integration of 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.

The architect will drive enterprise-grade AI platform development, ensuring seamless integration of 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 AutoGens 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.

Qualifications

• 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.

Required Skills

• 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.
• 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.

Preferred Skills

• Experience with additional AI frameworks and tools.
• Familiarity with cloud-based solutions and architectures.