01Overview
Core AI & Agentic AI Skills
Generative AI (Gen AI) solution design and delivery
Agentic AI architecture and implementation
Large Language Models (LLMs) and AI-powered applications
Agentic AI frameworks
LangChain
LangGraph
Semantic Kernel
Machine Learning (ML) architecture and deployment
Enterprise AI/ML solution architecture
Cloud & AI Platforms
Azure AI Services
Azure OpenAI Service
OpenAI technologies
Multi-cloud experience:
Microsoft Azure
AWS
Google Cloud Platform (GCP)
Solution Architecture & Deployment
Enterprise Architecture
End-to-end AI solution delivery (PoC to Production)
AI model deployment at scale
Reusable AI assets, accelerators, and frameworks development
AI Governance, Responsible AI, and Compliance
AI Security and Data Privacy
Engineering & DevOps
CI/CD pipelines
Docker
Kubernetes
Microservices Architecture
Production-grade AI application deployment
MLOps / LLMOps (strongly implied)
Leadership & Stakeholder Management
Technical leadership of AI teams
Architecture governance
Client-facing solution delivery
Stakeholder management
Cross-functional team leadership
Business requirement translation into AI solutions
Mentoring architects and engineering teams
Domain & Business Knowledge
Enterprise-scale digital transformation
Industry use cases involving
SAP
Salesforce
Finance
Supply Chain
Business Services / Shared Services environments
Experience Requirements
Master's degree in Computer Science, Engineering, Data Science, or related field (PhD preferred)
6+ years in Enterprise Architecture and Solution Delivery
Proven experience designing and deploying AI solutions at scale
Experience managing large AI programs and cross-functional teams .
