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GEN AI CLOUD TERRAFORM ENGINEER

  • Source: Indeed
  • UIDM
  • On-site
  • State of Telangāna, India
  • Full-Time
  • Mid level

Job Description

GenAI / Cloud / Terraform Engineer

Location: Hyderabad (Onsite – 5 Days/Week)

Employment Type: C2C

Priority: P1

Experience: 6+ Years

Job Summary

We are seeking an experienced GenAI / Cloud / Terraform Engineer to design, develop, and deploy enterprise-grade AI solutions leveraging Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, and cloud-native technologies. The ideal candidate will have strong expertise in Generative AI, cloud platforms (Azure preferred), Infrastructure as Code (Terraform), and agent orchestration frameworks to build scalable, secure, and reusable AI capabilities.

Experience Required

Total IT Experience: 6+ Years

Generative AI: 3+ Years

Cloud Platforms (Azure/AWS/GCP): 5+ Years

Terraform: 2+ Years

Key Responsibilities

Design, develop, and deploy enterprise AI/ML solutions using approved AI technologies and cloud platforms.

Build reusable AI capabilities, including copilots, AI agents, APIs, plugins, and domain-specific automation components.

Develop and operationalize AI-powered applications such as coding assistants, recommendation engines, enterprise search assistants, and workflow automation solutions.

Design and implement Retrieval-Augmented Generation (RAG) solutions for text-to-code, diagram-to-code, knowledge retrieval, recommendation systems, and enterprise automation.

Develop AI-powered search solutions, chatbots, and REST APIs to improve business productivity and user experience.

Design and implement AI agent-based systems featuring:

Tool invocation and function calling

Multi-step reasoning workflows

Autonomous task execution

Develop scalable AI solutions using OpenAI, LLMs, vector databases, embeddings, and indexing techniques.

Build and deploy AI workloads on cloud platforms, preferably Azure (AWS experience is also acceptable).

Develop and maintain MCP Servers for seamless integration with AI agents (e.g., Copilot Agent Mode).

Create reusable Terraform modules and Infrastructure as Code (IaC) frameworks for AI infrastructure.

Ensure secure coding standards, monitoring, logging, and operational excellence across AI applications.

Required Skills

Generative AI

Strong expertise in:

Large Language Models (LLMs)

OpenAI

Generative AI

Retrieval-Augmented Generation (RAG)

AI Agents

Experience building enterprise AI skills such as copilots, agents, APIs, reusable services, and plugins.

Hands-on experience with vector databases and semantic search implementations.

Experience with AI evaluation frameworks such as:

RAGAS

DeepEval

Experience implementing model fine-tuning techniques including:

LoRA

QLoRA

AI Agent Frameworks

Experience with one or more of:

LangGraph

AutoGen

CrewAI

Programming

Strong proficiency in at least one of:

Python

.NET

Node.js

Cloud & Infrastructure

Azure (Preferred)

AWS (Acceptable)

Terraform (Infrastructure as Code)

AI Integration

MCP Server development

Function Calling

Tool Invocation

Agent Orchestration

API Development

Preferred Qualifications

Experience building enterprise AI platforms or reusable AI frameworks.

Experience creating AI skill catalogs or internal developer platforms.

Experience developing reusable Terraform frameworks.

Experience standardizing Infrastructure as Code across enterprise teams.

Strong understanding of secure coding practices.

Experience with monitoring and observability tools such as Splunk.

Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.

Nice to Have

Azure OpenAI Services

Azure AI Foundry

Azure AI Search

Kubernetes (AKS/EKS)

Docker

CI/CD Pipelines

GitHub Actions or Azure DevOps

Prompt Engineering

Model Evaluation & Guardrails

Work Location: In person

Skills

  • Terraform
  • microsoft-azure
  • amazon-web-services
  • google-cloud-platform
  • mode
  • LangGraph
  • crewai
  • Python
  • NodeJS
  • splunk
  • azure-search
  • Kubernetes
  • Docker
  • Github
  • github-actions
  • azure-devops
  • guardrails
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