Fullstack Gen AI - Engineer

Iris Software; Dadri; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

Iris Software is hiring a Fullstack Gen AI - Engineer to design and implement Generative AI solutions in Noida. You will build AI-powered applications, integrate with cloud services, and implement agentic workflows supporting enterprise knowledge retrieval and automation.

The role requires strong Python, FastAPI, and security-focused API design, plus experience with LangChain/LangGraph for orchestration and a hands-on approach to model customization and evaluation.

Qualifications

• Experience with GenAI agentic frameworks and deployment patterns.
• Proficiency in integrating cloud apps and AI services.
• Hands-on with LangChain/LangGraph for AI workflows.

Responsibilities

• Develop GenAI solutions using Bedrock, Azure OpenAI, and Azure Foundry.
• Build RAG, Graph RAG, or Agentic AI workflows for enterprise data retrieval.
• Create AI-powered apps with Python and FastAPI APIs.
• Implement security, authentication, and scalable APIs.
• Configure AI agents, tool calling, and automated workflows.
• Orchestrate AI interactions with LangChain/LangGraph and semantic search.

Skills

GenAI agentic framework concepts

Cloud app integration deployment

AI agents tool calling

Azure AI Foundry

LangChain

LangGraph

Python

Tools

GitHub

Job description

Job Summary

Fullstack Gen AI - Engineer

Location

Noida

Company

Iris Software

Responsibilities

• Develop and implement Generative AI solutions using platforms such as Amazon Bedrock, Azure OpenAI Service, Azure AI Foundry, Grog, or AI Search Index services.
• Build Retrieval-Augmented Generation (RAG), Graph RAG, or Agentic AI solutions to support enterprise knowledge retrieval and intelligent automation use cases.
• Develop AI-powered applications leveraging Large Language Models (LLMs) aligned with business requirements.
• Develop secure AI services using Python and FastAPI, implement authentication, authorization, asynchronous APIs, request throttling, scheduling, multithreading, and scalable API design where applicable.
• Configure and implement AI agents, tool-calling mechanisms, and intelligent workflow automation solutions.
• Develop and maintain workflows using LangChain or LangGraph to orchestrate AI interactions and business processes.
• Implement prompt engineering, context management, and retrieval strategies to improve AI response quality and relevance.
• Support implementation of vector databases, semantic search, and prompt engineering techniques to improve retrieval quality and AI response accuracy where applicable.
• Support fine-tuning and model customization activities to enhance model performance for domain-specific use cases.
• Integrate AI applications with enterprise systems, databases, external APIs, cloud services, and Model Context Protocol (MCP)-based services where applicable to enable secure, scalable, and seamless business workflows.
• Perform testing, validation, and evaluation of AI-generated outputs to ensure quality, accuracy, and reliability.
• Monitor AI solution performance and support troubleshooting and optimization activities.
• Maintain technical documentation, prompt configurations, workflow definitions, and implementation artifacts.
• Collaborate with various teams and stakeholders to support successful AI solution delivery.
• Ensure AI solutions are reliable, scalable, maintainable, and aligned with business requirements.

Behavioral Competencies

• Demonstrates ownership and accountability while delivering high-quality AI solutions.
• Collaborate effectively with various teams and business stakeholders to ensure smooth delivery.
• Maintains a quality-first mindset while developing reliable and effective AI-powered applications.
• Applies strong analytical and problem-solving skills to resolve AI, retrieval, and workflow-related challenges.
• Shows adaptability and willingness to learn evolving AI technologies, frameworks, and industry trends.
• Communicates clearly by sharing progress, risks, assumptions, and dependencies proactively.
• Maintains attention to detail during AI solution development, testing, validation, and deployment activities.
• Works effectively in dynamic environments with changing priorities and evolving business requirements.
• Takes initiative in improving AI solution quality, automation effectiveness, and operational efficiency.
• Demonstrates a customer-centric mindset by delivering reliable, high-quality solutions.

Mandatory Competencies

• DevOps/Configuration Mgmt - DevOps/Configuration Mgmt - GitLab,Github, Bitbucket
• Cloud - Azure - Azure Devops, Azure Pipelines, Azure CLI
• User Interface - UI-React - React
• Data AI - GEN AI - Azure AI Foundry
• Data AI - GEN AI - Workflow Agentic Frameworks (LangChain / LangGraph)
• Data AI - GEN AI - Prompt Engineering / Vector Databases
• Data AI - GEN AI - Retrieval Augmented Generation (RAG) / Graph RAG / Agentic AI Systems
• Data AI - GEN AI - Fine tuning Model Customization / AI Agents Tool Calling
• Data AI - GEN AI - Python
• Data AI - GEN AI - Pandas
• Data AI - GEN AI - NumPy
• Data AI - GEN AI - Advanced GenAI Agentic Framework Concepts
• Data AI - GEN AI - Cloud Application Integration Deployment
• Beh - Communication and collaboration

Mandatory Skills

• Advanced GenAI Agentic Framework Concepts,Cloud Application Integration Deployment,AI Agents Tool Calling,Azure AI Foundry,Agentic AI Systems,LangChain,LangGraph

Additional Skills

• GitHub