Gen AI Developer_ IRIS Software, Noida | Immediate joiners

Iris Software; Dadri, Pune District, Gurugram District; Hybrid; INR 1,500,000 - 2,500,000; Full time

Job summary

IRIS Software Inc in Noida is seeking a GEN AI Developer to design and implement enterprise GenAI solutions across cloud platforms. The role demands hands-on work with LangGraph, LangChain, RAG, and agentic frameworks to deliver scalable AI services.

The position is hybrid with immediate joiners preferred and requires 6-8 years of experience in core GenAI engineering, cloud-native deployments, and prompt engineering.

Qualifications

• 6–8 years of relevant GenAI engineering experience.
• Strong programming skills in Python and prompt engineering.
• Hands-on with LangGraph, LangChain and RAG architectures.
• Experience with cloud platforms and AI service integration (Azure, Bedrock, AI Foundry).

Responsibilities

• Design and develop enterprise Generative AI solutions on cloud platforms like Azure OpenAI Service and others.
• Define AI solution architectures aligned to business goals.
• Implement RAG, Graph RAG, and Agentic AI architectures for enterprise use cases.
• Lead development of intelligent AI agents, tool-calling workflows, and autonomous tasks frameworks.
• Design multi-agent orchestration using LangGraph; evaluate AutoGen or CrewAI when suitable.
• Design and optimize prompt strategies, context orchestration, and response generation frameworks.
• Develop pipelines for prompt engineering, vector databases, and semantic search for GenAI apps.
• Build workflows using LangChain or LangGraph for scalable AI applications.
• Ensure secure, scalable cloud-native AI integration with APIs, databases, messaging, and event-driven patterns.
• Lead model fine-tuning and domain-specific customization efforts.

Skills

Python

GenAI & Agentic Frameworks

Cloud Integration & Deployment

FastAPI

Azure OpenAI Service

RAG

AI Agents & Tool Calling

LangGraph

LangChain

Prompt Engineering

Job description

IRIS Software Inc is seeking GEN AI Developer _ IRIS Software, Noida || Immediate joiners only || Hybrid Opportunity

Total Experience: 6-8 years

Shift : U.K(12 Pm to 9 pm)

Notice Period : Immediate joiners will preferred

Pls go through the JD below

Mandatory Skills:

Python, Advanced GenAI & Agentic Framework Concepts, Cloud Application Integration & Deployment, FastAPI Framework, Azure OpenAI Service, Retrieval-Augmented Generation (RAG), AI Agents & Tool Calling, LangGraph, LangChain, Prompt Engineering.

Key Responsibilities

• Design and develop enterprise Generative AI solutions using Amazon Bedrock, Azure OpenAI Service, Azure AI Foundry, Grog, or AI Search Index platforms.
• Define AI solution architectures and implementation approaches aligned with business and technical objectives.
• Design and implement Retrieval-Augmented Generation (RAG), Graph RAG, and Agentic AI architectures for enterprise use cases.
• Lead development of intelligent AI agents, tool-calling workflows, and autonomous task execution frameworks.
• Design and implement multi-agent orchestration solutions using frameworks such as LangGraph and evaluate emerging frameworks such as AutoGen or CrewAI where appropriate.
• Design and optimize prompt strategies, retrieval mechanisms, context orchestration, and response generation frameworks.
• Design prompt engineering pipelines, vector database integration, semantic search solutions, and Retrieval-Augmented Generation architectures supporting enterprise AI applications.
• Design and implement workflows using LangChain or LangGraph to support scalable AI application development.
• Design scalable AI engineering architectures incorporating authentication, authorization, asynchronous processing, scheduling, multithreading, API governance, and enterprise deployment best practices.
• Lead fine-tuning and model customization initiatives to improve domain-specific AI performance.
• Define AI integration patterns and deployment approaches for enterprise application ecosystems.
• Design cloud-native AI integration patterns supporting enterprise APIs, databases, messaging platforms, and event-driven architectures.
• Establish evaluation frameworks for AI response quality, reliability, relevance, and consistency.
• Design Human-in-the-Loop (HITL) workflows and evaluation mechanisms to improve AI quality, governance, and business reliability.
• Review AI solution designs to ensure adherence to engineering standards, scalability, maintainability, and responsible AI practices.
• Troubleshoot complex AI workflow, retrieval, orchestration, and model behavior challenges through detailed root cause analysis.
• Mentor team members on GenAI frameworks, RAG architectures, agentic systems, and AI engineering best practices.
• Drive continuous improvement initiatives focused on AI solution quality, innovation, and operational effectiveness.