GenAI / Cloud / Terraform Engineer

Delphic; India; Remote; INR 3,500,000 - 6,000,000; Full time

Job summary

Delphic is seeking an experienced GenAI / Cloud / Terraform Engineer to design and deploy enterprise AI-powered solutions in cloud-native environments.

You will work with Generative AI, LLMs, RAG, MCP, and agentic AI, with hands-on Terraform and cloud deployment experience.

Qualifications

• 8+ years of IT experience with 3+ years in GenAI and 5+ years in cloud technologies.
• Proven production deployments of AI-powered applications.
• Familiarity with vector databases, embeddings, and semantic search.
• Exposure to model fine-tuning techniques (LoRA/QLoRA).
• Experience with agent orchestration frameworks (LangGraph, AutoGen, CrewAI).
• Knowledge of MCP servers and Model Context Protocol.

Responsibilities

• Design, develop, and deploy GenAI/LLM-based solutions for enterprise use cases.
• Build RAG-based apps, AI-powered search, chatbots, copilots, and workflow automation.
• Develop AI agents and multi-agent systems with tool invocation and autonomous task execution.
• Implement MCP servers to integrate AI agents with enterprise tools.
• Create reusable AI components, APIs, plugins, and AI skills for enterprise apps.
• Work with vector databases, embeddings, and indexing for retrieval accuracy.
• Deploy AI workloads on cloud platforms (Azure/AWS/GCP) and manage IaC with Terraform.
• Define AI evaluation metrics using RAGAS/DeepEval and ensure secure coding practices.
• Troubleshoot, monitor, and log across AI apps and cloud deployments.

Skills

Generative AI

RAG & Agentic AI

MCP

Cloud Architecture

Terraform IaC

Python

Node.js

Troubleshooting

Tools

LangGraph

AutoGen

Job description

Job Description: GenAI / Cloud / Terraform Engineer

Experience: 8+ Years. GenAI Experience: 3+ Years. Cloud Experience: 5+ Years. Terraform Experience: 2+ Years. Work Mode: Remote. Working Hours: 11:00 AM – 9:00 PM.

Role Overview

We are looking for an experienced GenAI / Cloud / Terraform Engineer to design, develop, and deploy enterprise‑grade AI‑powered solutions in cloud‑native environments. The ideal candidate should have strong hands‑on expertise in Generative AI, Large Language Models (LLMs), Retrieval‑Augmented Generation (RAG), Model Context Protocol (MCP), and Agentic AI, along with practical knowledge of cloud architecture and Terraform.

Key Responsibilities

• Design, develop, and deploy Generative AI and LLM‑based solutions for enterprise use cases.
• Build RAG‑based applications, AI‑powered search solutions, chatbots, copilots, and workflow automation tools.
• Develop AI agents and multi‑agent systems with tool invocation, function calling, and autonomous task execution.
• Implement MCP servers to integrate AI agents with enterprise tools and services.
• Develop reusable AI components, APIs, plugins, and AI skills for enterprise applications.
• Work with vector databases, embeddings, and indexing techniques to optimize retrieval accuracy and performance.
• Implement agent orchestration using frameworks such as LangGraph, AutoGen, or CrewAI.
• Deploy and manage AI workloads on cloud platforms, preferably Microsoft Azure, or AWS/GCP.
• Use Terraform and Infrastructure as Code (IaC) practices to provision and manage cloud infrastructure.
• Define and implement AI evaluation metrics using tools such as RAGAS and DeepEval.
• Troubleshoot and resolve issues across AI applications, cloud infrastructure, and deployments.
• Apply secure coding practices and implement monitoring, logging, and alerting mechanisms.

Mandatory Skills

• Generative AI: Strong hands‑on experience with GenAI, LLMs, and OpenAI.
• RAG & Agentic AI: Experience building RAG pipelines, AI agents, and multi‑agent systems.
• MCP: Hands‑on experience with Model Context Protocol and MCP server development.
• Cloud: Strong understanding of cloud architecture and deployment, preferably Azure.
• Terraform: Working knowledge of Terraform and Infrastructure as Code (IaC).
• Programming: Proficiency in Python, .NET, or Node.js.
• Troubleshooting: Strong debugging, analytical, and problem‑solving skills.

Required Qualifications

• 8+ years of overall IT experience, including 3+ years in GenAI, 5+ years in cloud technologies, and 2+ years in Terraform.
• Experience building and deploying production‑ready AI‑powered applications.
• Knowledge of agent orchestration frameworks such as LangGraph, AutoGen, or CrewAI.
• Experience with vector databases, embeddings, and semantic search.
• Familiarity with AI evaluation frameworks such as RAGAS and DeepEval.
• Exposure to model fine‑tuning techniques such as LoRA/QLoRA.

Good to Have

• Experience with Specification‑Driven Development (SDD).
• Experience developing reusable Terraform modules and standardized IaC frameworks.
• Knowledge of enterprise AI platforms and reusable AI skill catalogs.
• Experience with monitoring and logging tools such as Splunk.
• Experience implementing secure, scalable, and highly available cloud‑native solutions.