Required Qualifications

Education
Bachelor's or Master's degree in Engineering, Computer Science, Data Science, Information Systems, Supply Chain, Operations Management, or a related field.

Experience
5+ years of experience in Process Engineering, Automation, Digital Transformation, or Operations Excellence.
3+ years of experience in AI/ML, Generative AI, Agentic AI, or intelligent automation solutions.
Experience in Supply Chain, Manufacturing, Logistics, Operations, or Enterprise Transformation programs preferred.
Proven track record of delivering AI-enabled business outcomes at scale.

Technical Skills

AI & Agentic Technologies
Generative AI and Large Language Models (LLMs)
Agentic AI frameworks (AutoGen, Microsoft Agent Framework, CrewAI, LangGraph, Google ADK, etc.)
Prompt Engineering and AI Evaluation Frameworks
Retrieval-Augmented Generation (RAG)
Vector Databases and Embedding Models

Development & Integration
Python and API Integration
AI Orchestration Platforms
Data Pipelines and Workflow Automation
Enterprise System Integration (ERP, SCM, CRM)

Observability & Analytics
AI Telemetry and Monitoring
Power BI, Tableau, or equivalent analytics platforms
Performance optimization and operational dashboards

Tools
Jira, Azure DevOps, Confluence
Azure AI Services, OpenAI,



Amazon Bedrock, or similar AI platforms
Cloud platforms (Azure, AWS, GCP)

Preferred Certifications
Generative AI or AI/ML Certifications
Lean Six Sigma Green Belt or Black Belt
APICS / Supply Chain Certifications
Cloud Certifications (Azure, AWS, Google Cloud)
Process Automation or Digital Transformation Certifications

Key Competencies
Systems Thinking and Structured Problem Solving
Solid Analytical and Critical Thinking Skills
Process Re-engineering and Continuous Improvement Mindset
Stakeholder Management and Executive Communication
Business Process Transformation
AI Strategy and Innovation Leadership
Cross-functional Collaboration and Change Managemen

Success Metrics
Increased AI adoption and automation across business processes
Improvement in agent accuracy, reliability, and task completion rates
Reduction in manual effort and process cycle times
Enhanced supply chain and operational performance metrics
Improved AI governance, observability, and compliance adherence
Increased retrieval accuracy and response quality in RAG implementations
Optimized AI operating costs and platform efficiency
Measurable business value through AI-enabled transformation initiatives

📌 Ai Process Catalyst Bengaluru
🏢 Ascendion
📍 Bengaluru