Ai Ml Engineer

Tavant

Hyderabad

On-site

INR 1,800,000 - 2,800,000

Full time

7 days ago
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Job summary

Tavant is seeking an experienced AI/ML Engineer to design, develop, and deploy enterprise-grade Generative AI and Agentic AI solutions. The role focuses on building scalable RAG pipelines, multi-agent workflows, and MCP-enabled integrations while leveraging Azure AI technologies.

Responsibilities include developing applications with Python and Azure OpenAI, implementing LangGraph-based workflows, and delivering scalable AI solutions on the Azure cloud.

Qualifications

  • Experience designing and implementing production-grade AI/ML applications.
  • Strong knowledge of Azure AI services and cloud deployments.
  • Proficiency in Python and integrating AI solutions into enterprise systems.

Responsibilities

  • Develop AI applications using Python, Azure OpenAI, and RAG architectures.
  • Design and implement agentic workflows using LangGraph and MCP.
  • Build and optimize vector search and knowledge retrieval systems.
  • Integrate AI agents with enterprise tools and APIs through MCP Gateway.
  • Deploy, monitor, and scale AI solutions on Azure cloud.
  • Collaborate with product and engineering teams to deliver production-ready AI applications.

Skills

Python
Azure OpenAI
RAG architectures
LangGraph
Multi-agent workflows
Vector search

Tools

MCP Gateway

Job description

Role & responsibilities

Job Description

We are looking for an experienced AI/ML Engineer to design, develop, and deploy enterprise-grade Generative AI and Agentic AI solutions. The candidate will build scalable RAG pipelines, multi-agent workflows using LangGraph, and MCP-enabled integrations while leveraging Azure AI technologies.

Responsibilities
  • Develop AI applications using Python, Azure OpenAI, and RAG architectures.
  • Design and implement agentic workflows using LangGraph and MCP.
  • Build and optimize vector search and knowledge retrieval systems.
  • Integrate AI agents with enterprise tools and APIs through MCP Gateway.
  • Deploy, monitor, and scale AI solutions on Azure cloud.
  • Collaborate with product and engineering teams to deliver production-ready AI applications.
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