Role: GenAI / Cloud / Terraform Engineer
Experience: 8+ Years
Work Mode: Remote
Working Hours: 11:00 AM – 9:00 PM IST

Job Summary:

We are looking for experienced GenAI / Cloud / Terraform Engineers who can design, develop, deploy, and operationalize up-to-date AI-powered solutions in cloud-native environments.

The ideal candidate should have strong hands-on expertise in Generative AI, LLMs, RAG, MCP, Agentic AI, cloud architecture, and Terraform/IaC, along with the ability to build enterprise-grade AI capabilities and reusable components.

Mandatory Skills:

Generative AI / GenAI

Large Language Models (LLMs)

RAG (Retrieval-Augmented Generation)

MCP (Model Context Protocol) / MCP Servers

Agentic AI / Multi-Agent Systems

Cloud Architecture – Azure preferred

Terraform / Infrastructure as Code (IaC)

Strong programming skills in Python, .NET, or Node.js

Vector databases and indexing techniques

Strong debugging, troubleshooting, and problem-solving skills

Key Responsibilities

Design and develop AI/ML and Generative AI solutions using enterprise-approved technologies.

Develop reusable AI capabilities such as:

Copilots

AI agents

APIs

Plugins

Domain-specific automation components

Build and operationalize AI-powered solutions including:

Coding assistants

Recommendation engines

Search assistants

Workflow automation

AI-powered chatbots

Develop RAG-based GenAI solutions for use cases such as text-to-code, diagram-to-code, recommendations, and automation.

Design and implement AI-powered search solutions, chatbots, and APIs.

Design and develop solutions using OpenAI, LLMs, RAG, and Agentic AI.

Implement vector databases and indexing strategies to optimize AI applications.

Deploy and manage AI workloads in Azure or AWS cloud environments.

Design agent-based AI systems supporting:





Tool invocation and function calling

Multi-step reasoning and decision workflows

Autonomous task execution

Agent-to-agent interactions

Work with agent orchestration frameworks such as LangGraph, AutoGen, or CrewAI.

Develop and implement MCP Servers for integration with AI agents and enterprise applications.

Define and implement evaluation strategies for AI and agentic systems.

AI Evaluation & Optimization

Experience with AI evaluation frameworks such as RAGAS and DeepEval.

Define metrics to evaluate:

Accuracy

Reliability

Relevance

Response quality

Agent performance

Memory retention

Apply prompt/context engineering techniques to improve AI system performance.

Experience with model fine-tuning techniques such as LoRA / QLoRA is preferred.

Cloud & Terraform Responsibilities

Design and implement cloud-native AI solutions, preferably on Azure.

Develop reusable Terraform modules and frameworks for AI workloads.

Standardize Infrastructure as Code templates across teams.

Support deployment, configuration, and management of cloud AI services.

Ensure cloud solutions follow security, scalability, reliability, and cost-optimization best practices.

Support internal developer platforms for AI workloads.

Required Qualifications

8+ years of overall professional experience.

3+ years of hands-on GenAI experience.

5+ years of cloud experience across Azure, AWS, or GCP.

2+ years of Terraform/IaC experience.





Proven experience designing and developing reusable AI components such as copilots, agents, plugins, APIs, and services.

Strong expertise in Generative AI, OpenAI, LLMs, RAG, and Agentic AI.

Hands-on experience developing MCP Servers.

Experience with vector databases and indexing techniques.

Strong programming experience in Python, .NET, or Node.js.

Hands-on experience with Azure or AWS.

Strong understanding of cloud architecture and cloud-native application development.

Strong troubleshooting and problem-solving capabilities.

Preferred Skills:

Experience building enterprise-grade AI skill catalogs, developer platforms, or reusable AI frameworks.

Experience developing reusable Terraform frameworks or internal developer platforms for AI workloads.

Experience standardizing IaC templates across multiple teams.

Knowledge of Specification-Driven Development (SDD).

Experience building solutions from functional and technical specifications.

Experience with Splunk or similar monitoring, logging, and alerting platforms.

Strong understanding of secure coding and cloud security practices.

Advanced degree in Computer Science, Engineering, or a related field.

Key Technology Stack

GenAI: Generative AI, LLMs, OpenAI, RAG, Prompt Engineering

Agentic AI: MCP, MCP Servers, Multi-Agent Systems, LangGraph, AutoGen, CrewAI

AI Evaluation: RAGAS, DeepEval

Programming: Python, .NET, Node.js

Cloud: Azure, AWS, GCP

Infrastructure: Terraform, IaC

Data: Vector Databases, Indexing

Monitoring: Splunk

AI Fine-Tuning: LoRA, QLoRA

Pay: ₹90,000.00 - ₹100,000.00 per month

Experience:

- Terraform: 2 years (Required)
- Cloud: 5 years (Required)
- Generative AI: 3 years (Required)

Work Location: Remote

📌 Generative AI Engineer (India)
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