Agentic AI Architect

Job Summary

We are seeking an experienced Agentic AI Architect to design, build, and scale next-generation AI solutions leveraging LLMs, AI Agents, Multi-Agent Systems, RAG architectures, and Generative AI platforms. The ideal candidate will have strong expertise in AI/ML architecture, cloud platforms, orchestration frameworks, and enterprise application integration.

This role will be responsible for defining enterprise AI strategy, architecting autonomous AI agent ecosystems, ensuring governance and security, and driving AI transformation initiatives across business domains.

Key Responsibilities

AI & Agentic Architecture

• Define enterprise-wide Agentic AI architecture and technology roadmap.
• Design and implement autonomous AI Agents and Multi-Agent Systems for complex business workflows.
• Architect solutions using LLMs, RAG (Retrieval-Augmented Generation), Knowledge Graphs, and Vector Databases.
• Establish reusable AI frameworks, accelerators, and reference architectures.
• Design AI agent collaboration, planning, reasoning, memory, and tool integration capabilities.

Generative AI Solutions

• Architect enterprise GenAI solutions using OpenAI, Azure OpenAI, Anthropic Claude, Gemini, Llama, or similar models.
• Design prompt engineering, AI orchestration, and model optimization strategies.
• Build AI copilots, virtual assistants, intelligent automation, and decision-support systems.

AI Engineering & Cloud

• Lead deployment of AI solutions on Azure, AWS, or GCP.
• Design scalable AI infrastructure using Kubernetes, Docker, MLOps, and CI/CD pipelines.
• Implement AI observability, monitoring, guardrails, governance, and security frameworks.
• Integrate AI agents with enterprise applications, APIs, databases, ERP, CRM, and workflow platforms.

Stakeholder & Leadership

• Partner with business leaders to identify high-value AI use cases.
• Drive AI innovation workshops, architecture reviews, and technical mentoring.
• Lead technical teams comprising AI Engineers, Data Scientists, ML Engineers, and Developers.
• Present AI transformation strategies to CXO-level stakeholders.

Mandatory Skills

Agentic AI & GenAI

• Agentic AI Architecture
• Multi-Agent Systems
• Large Language Models (LLMs)
• Prompt Engineering
• AI Agent Frameworks (LangChain, LangGraph, AutoGen, CrewAI, LlamaIndex)
• Retrieval-Augmented Generation (RAG)
• Vector Databases (Pinecone, Weaviate, ChromaDB, FAISS)
• Knowledge Graphs

AI/ML Technologies

• Python
• Machine Learning & Deep Learning
• NLP
• Model Fine-tuning
• AI Evaluation Frameworks

Cloud & DevOps

• Azure AI Services / Azure OpenAI (Preferred)
• AWS Bedrock / SageMaker
• Google Vertex AI
• Docker & Kubernetes
• CI/CD Pipelines
• MLOps Platforms (MLflow, Kubeflow)

ntegration & Data

• REST APIs
• Event-Driven Architecture
• Microservices
• Data Lakes & Data Warehouses
• SQL & NoSQL Databases