About the Role As an AI Architect, you will define the strategic architecture for enterprise AI initiatives, including Generative AI, Agentic AI, Machine Learning platforms, and intelligent automation solutions. You will work closely with business leaders, engineering teams, data scientists, and cloud architects to deliver secure, scalable, and production-ready AI systems. Key Responsibilities Define end-to-end architecture for AI, Gen AI, Agentic AI, and ML platforms. Design and implement scalable LLM-powered and multi-agent systems. Establish AI architecture standards, governance, security, and best practices. Drive technical architecture discussions across engineering and business stakeholders. Evaluate and recommend AI tools, frameworks, cloud services, and platforms. Ensure scalability, reliability, compliance, and performance of enterprise AI solutions. Define AI platform roadmaps and enterprise integration strategies. Mentor architects, engineers, and AI practitioners across teams. Guide organizations through large-scale AI transformation initiatives. Required Qualifications12+ years of experience in software engineering, solution architecture, or enterprise architecture. Strong expertise in AI/ML architecture and distributed system design. Hands-on experience with Large Language Models (LLMs), RAG architectures, and Agentic AI systems. Experience designing and deploying multi-agent AI solutions. Strong understanding of data engineering, ML lifecycle, MLOps, and AI governance. Experience with enterprise integration patterns, microservices, APIs, and event-driven architectures. Knowledge of AI security, compliance, privacy, and responsible AI principles. Proven ability to lead technical teams and architecture decisions. Technical Skills AI & Gen AIOpen AI, Azure Open AI, Claude, Gemini, Llama RAG (Retrieval-Augmented Generation) Prompt Engineering Vector Databases Knowledge Graphs AI Evaluation & Monitoring Agentic AILang Chain Lang Graph Crew AIAuto Gen Semantic Kernel Multi-Agent Orchestration Frameworks Cloud Platforms AWS (Bedrock, Sage Maker) Microsoft Azure (Azure Open AI, AI Foundry, AI Search) Google Cloud (Vertex AI) Data & MLOps Databricks Snowflake MLflow Airflow Kubeflow Preferred Qualifications Experience leading enterprise AI transformation programs. Experience building AI platforms serving multiple business units. Relevant cloud certifications (AWS, Azure, GCP). Experience working in regulated industries.