Azure Solution Architect GenAI Agentic AI

Job Description

We are seeking a highly experienced Azure Solution Architect – GenAI / Agentic AI to lead the design, architecture, and implementation of enterprise-grade Generative AI and Agentic AI solutions on Microsoft Azure. The ideal candidate will possess deep expertise in Azure AI services, Large Language Models (LLMs), cloud-native architectures, intelligent automation, and enterprise integration frameworks.

In this role, you will architect scalable AI platforms, autonomous AI agents, and GenAI-powered enterprise applications that drive digital transformation and operational efficiency. You will work closely with business stakeholders, AI engineers, cloud teams, and enterprise architects to define AI strategies, solution roadmaps, and implementation best practices.

The position requires strong leadership, hands-on technical expertise, and a strategic understanding of enterprise AI adoption, governance, and security.

Key Responsibilities

• Design and architect enterprise-grade Generative AI and Agentic AI solutions using Microsoft Azure services.
• Lead the development of autonomous AI agents, intelligent workflows, and AI-powered enterprise applications.
• Architect scalable AI platforms leveraging:
• Azure OpenAI Service
• Azure AI Studio
• Azure Machine Learning
• Azure Cognitive Services
• Azure Kubernetes Service (AKS)
• Design and implement Retrieval-Augmented Generation (RAG) architectures and vector search solutions.
• Build secure and scalable AI orchestration frameworks using LangChain, Semantic Kernel, AutoGen, CrewAI, or similar technologies.
• Define enterprise AI architecture standards, governance models, security controls, and responsible AI practices.
• Collaborate with business and technical teams to identify AI use cases and translate requirements into scalable cloud solutions.
• Design integration strategies between AI platforms and enterprise systems such as CRM, ERP, ITSM, and data platforms.
• Optimize AI solution performance, scalability, latency, and operational efficiency.
• Lead cloud migration and modernization initiatives involving AI and intelligent automation.
• Mentor development and architecture teams on Azure AI best practices and cloud-native design principles.
• Support pre-sales activities, solution proposals, technical presentations, and client workshops when required.
• Stay updated on emerging GenAI, Agentic AI, and Azure ecosystem advancements.

Required Skills and Qualifications

Azure & Cloud Architecture

• Strong experience designing enterprise solutions on Microsoft Azure.
• Hands-on expertise with:
• Azure OpenAI Service
• Azure AI Studio
• Azure Machine Learning
• Azure Cognitive Search
• Azure Functions
• Azure Logic Apps
• Azure API Management
• Azure Data Factory
• Azure Synapse Analytics
• Azure Kubernetes Service (AKS)
• Strong understanding of cloud-native architectures, microservices, and distributed systems.
• Experience with Infrastructure as Code (IaC):
• Terraform
• ARM Templates
• Bicep

GenAI & Agentic AI Expertise

• Strong experience with Large Language Models (LLMs):
• GPT
• Claude
• Gemini
• Llama
• Hands-on experience building GenAI and Agentic AI applications.
• Expertise in:
• Prompt Engineering
• Retrieval-Augmented Generation (RAG)
• Vector Databases
• AI Memory Management
• Tool Calling
• Multi-Agent Systems
• AI Evaluation and Observability
• Experience with AI orchestration frameworks:
• LangChain
• Semantic Kernel
• CrewAI
• AutoGen

Software Engineering & DevOps

• Strong programming experience in:
• Python
• C#
• JavaScript/TypeScript
• Experience building REST APIs, event-driven systems, and enterprise integrations.
• Familiarity with:
• Docker
• Kubernetes
• CI/CD pipelines
• GitHub Actions
• Azure DevOps
• Experience with MLOps and AI lifecycle management.

Data & Integration

• Experience with structured and unstructured data platforms.
• Familiarity with:
• PostgreSQL
• Cosmos DB
• Redis
• Elasticsearch
• Vector Databases (Pinecone, Weaviate, ChromaDB, FAISS)
• Experience integrating AI systems with enterprise applications and APIs.

Leadership & Soft Skills

• Proven experience leading architecture and enterprise transformation initiatives.
• Strong communication and stakeholder management skills.
• Ability to work with cross-functional teams and executive leadership.
• Strong analytical, problem-solving, and decision-making capabilities.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Information Technology, Artificial Intelligence, or related field.
• 8+ years of experience in software engineering, cloud architecture, or enterprise solution architecture.
• 3+ years of hands-on experience with AI/ML, GenAI, or intelligent automation solutions.
• Proven experience delivering enterprise-scale Azure cloud solutions.
• Microsoft Azure certifications are highly preferred:
• Azure Solutions Architect Expert
• Azure AI Engineer Associate
• Azure Data Engineer Associate

Preferred Qualifications

• Experience in Telecom, BFSI, Healthcare, Manufacturing, or Enterprise Digital Transformation domains.
• Familiarity with AI governance, compliance, and responsible AI frameworks.
• Experience with conversational AI, copilots, and enterprise AI assistants.
• Exposure to Knowledge Graphs, Graph AI, and semantic search architectures.
• Experience with hybrid cloud or multi-cloud AI deployments.

Contributions to AI open-source projects or technical communities are a plus.