GENAI-Agentic AI Architect

Birlasoft; Bajidpur; Presencial; INR 4.000.000 - 7.000.000; Jornada completa

Descripción de la vacante

Birlasoft is seeking an experienced GENAI Agentic AI Architect to design secure, scalable GenAI solutions on Microsoft Azure. The role requires hands-on expertise with Azure OpenAI, multi-agent frameworks, LLM orchestration, and RAG, plus Python-based microservices.

You will define reference architectures, lead complex implementations, and drive enterprise adoption across major workloads. Strong focus on security, reliability, observability, and cost optimization, with mentoring responsibilities

Formación

• Over 15 years of technology experience with deep Azure architecting.
• Strong hands-on GenAI, Agentic AI, and LLM orchestration skills.
• Experience with RAG, vector databases, and multi-agent systems.
• Proficient in Python frameworks such as FastAPI or Django.
• Experience with Azure AI services and enterprise-grade security.

Responsabilidades

• Architect end-to-end GenAI and Agentic AI solutions on Azure.
• Define reference architectures and drive complex implementations.
• Lead enterprise adoption of GenAI capabilities and guardrails.
• Design multi-agent systems covering planning, memory, and tool invocation.
• Develop reusable patterns for orchestration and cloud-native GenAI.
• Mentor teams and provide architecture guidance.

Conocimientos

GenAI

Agentic AI

LLM orchestration

RAG

Multi-agent orchestration

Cloud native engineering

Herramientas

Azure OpenAI

Azure AI Foundry

Azure Agent Service

Azure Machine Learning

LangGraph

CrewAI

FastAPI

Django

Azure DevOps

AKS

Azure Functions

Azure Monitor

Log Analytics

Cosmos DB

PostgreSQL pgvector

Redis

Azure AI Search

Descripción del empleo

GENAI-Agentic AI Architect

Description:

Area(s) of responsibility

Job Title

GENAI Agentic AI Architect Azure

Experience

15 Plus Years

Location

Hyderabad, Pune, Chennai, Bengaluru, Mumbai, Noida

Job Description

We are looking for an experienced GenAI and Agentic AI Architect with strong hands on expertise in Microsoft Azure AI services, multi agent frameworks, LLM orchestration, RAG, Python, and cloud native engineering.

The role will focus on architecting secure, scalable, production grade GenAI solutions, defining reference architectures, leading complex implementations, and driving enterprise adoption of GenAI and Agentic AI capabilities.

Key Responsibilities

• Architect end to end GenAI and Agentic AI solutions using Azure OpenAI, Azure AI Foundry, Azure Agent Service, Microsoft Agent Framework, Azure Machine Learning, LangGraph, and CrewAI.
• Design multi agent systems covering planning, reasoning, memory, state management, tool invocation, human review, and complex workflow orchestration.
• Architect enterprise RAG solutions using Azure AI Search, vector search, Cosmos DB, PostgreSQL pgvector, and Redis.
• Design prompt pipelines, embedding workflows, retrieval strategies, context enrichment, tool integrations, model evaluation, and AI guardrails.
• Build Python based microservices using FastAPI or Django and integrate them with Azure AI and enterprise applications.
• Define LLMOps and deployment practices using Azure Machine Learning, Azure DevOps, GitHub Actions, AKS, Azure Functions, Azure Monitor, Application Insights, and Log Analytics.
• Define architecture standards for security, reliability, scalability, observability, performance, content safety, and cost optimization.
• Lead architecture reviews, threat modeling, performance benchmarking, technical prototypes, and production readiness.
• Develop reusable architecture patterns and accelerators for multi agent orchestration, RAG, enterprise integration, and cloud native GenAI solutions.
• Mentor technical teams and provide architecture guidance across complex GenAI programs.

Required Skills

• 15 plus years of technology experience with strong Azure architecture and engineering expertise.
• Strong experience with GenAI, Agentic AI, Azure OpenAI, Azure AI Foundry, Azure Agent Service, Azure Machine Learning, LangGraph, and CrewAI.
• Expertise in RAG, embeddings, vector databases, multi agent orchestration, LLMOps, and model evaluation.
• Strong Python experience using FastAPI or Django.
• Experience with Azure AI Search, Cosmos DB, AKS, Functions, API Management, Event Grid, and Service Bus.
• Strong knowledge of Azure security, distributed systems, scalability, performance, and cost optimization.
• Azure Solutions Architect certification preferred.