Description

Key Responsibilities

• Define and implement enterprise AI architecture frameworks, standards, and best practices
• Design end-to-end GenAI solutions leveraging Claude, Gemini, OpenAI, and other foundation models
• Architect RAG, agentic AI, multi-agent systems, vector databases, and knowledge management solutions
• Architect AI solutions across Azure and AWS environments
• Define AI governance, security, compliance, and risk management frameworks
• Serve as a trusted advisor to executive leadership on AI strategy and emerging technologies
• Mentor architects, engineers, and data science teams

Required Skills

• Foundation Models: Anthropic Claude, Google Gemini, OpenAI, multi-model orchestration
• GenAI Techniques: Prompt engineering, fine-tuning, RAG, AI agents, agentic workflows
• Vector Databases: Pinecone, Weaviate, Milvus, Chroma, Azure AI Search
• Frameworks: LangChain, LangGraph, LlamaIndex
• Azure: Azure OpenAI Service, Azure AI Foundry, Azure Machine Learning, AKS, Azure Data Services, Azure Security
• AWS: Amazon Bedrock, Amazon SageMaker, AWS Lambda, ECS/EKS, AWS Data and Analytics, AWS Security and Governance
• Programming: Python, SQL, REST APIs, Microservices Architecture, CI/CD, DevOps
• Ops: MLOps, LLMOps, model monitoring and evaluation

Preferred Skills

• Experience in regulated industries: healthcare, financial services, defense, or technology
• Enterprise AI governance and Responsible AI frameworks
• Integration of AI solutions with ERP, CRM, and enterprise systems
• Master's degree in Computer Science, AI, Data Science, or related field

Preferred Certifications

• Microsoft Certified: Azure Solutions Architect Expert or Azure AI Engineer Associate
• AWS Certified Solutions Architect Professional or Machine Learning Specialty
• Google Professional Cloud Architect or Professional Machine Learning Engineer

Key Skills

Education

Master's degree