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Softpath Technologies - Azure Solution Architect - Generative AI

SOFTPATH TECH SOLUTIONS PVT LTD
Multiple Locations
11 - 12 Years
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3.8white-divider16+ Reviews

Posted on: 25/11/2025

Job Description

Project-Specific Prerequisite Skills (Must Have) :

- Azure Cloud Architecture

- Python

- Azure OpenAI

- 2+ years of GenAI experience

- Hands-on experience in designing and implementation

Job Description Enterprise Azure Solution Architect (GenAI / Agentic AI) :


We are seeking a highly experienced Azure Solution Architect with a strong background in Generative AI (GenAI), AI Agents, Agentic AI, Retrieval-Augmented Generation (RAG), and Large Language Models (LLMs).


The ideal candidate will have extensive experience in Azure Cloud and AI/ML technologies, with a proven track record of designing and implementing complex AI solutions, guiding development teams, and ensuring successful deployment in fast-paced environments.

Experience Required :

- 15 years total experience in IT and software development

- 8 years of hands-on experience in Azure Cloud and AI/ML technologies

- Minimum 2 years of experience in Generative AI (GenAI), AI Agents, Agentic AI, Retrieval-Augmented Generation (RAG), Large Language Models (LLMs), and related technologies

- Hands-on experience in implementing design architecture and assisting developers in development and deployment

- Proven ability to guide developers, resolve technical issues, assist in debugging, and ensure timely delivery and deployment of solutions

Technical Skills & Responsibilities :

- Design and implement Azure-based solution architectures for GenAI applications

- Develop and deploy AI Agents using LangChain and LangGraph

- Implement RAG pipelines using Azure OpenAI Services, Vector Embeddings, and Azure AI Search

- Architect data solutions using Azure Cosmos DB and Azure Blob Storage

- Hands-on Python development for AI/ML and GenAI applications

- Create rapid Proof-of-Concepts (POCs) based on CXO-level discussions

- Collaborate with cross-functional teams to implement and deliver scalable and secure AI solutions based on the design architecture

- Ensure best practices in security using Azure Key Vault and Role-Based Access Control (RBAC)

Tech Stack :

- Cloud: Microsoft Azure

- GenAI / LLMs: Azure OpenAI Services, GPT models

- AI Agents: LangChain, LangGraph

- RAG: Azure AI Search, Vector Embeddings

- Data: Azure Cosmos DB, Azure Blob Storage

- Languages: Python, SQL

- Tools: VS Code, Git, Azure DevOps

- Security: Azure Key Vault, RBAC


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