Gen AI Fullstack - Lead

Iris Software, Inc.; Dadri; On-site; INR 1,800,000 - 3,000,000; Full time

Job summary

Iris Software, Inc. is seeking a Gen AI Fullstack - Lead to drive enterprise Generative AI strategy from Noida and lead architecture across cloud platforms. You will define standards for RAG, multi-agent systems, and secure deployment, guiding teams through GEN AI adoption and governance.

Lead design, governance, and implementation of agent-based AI solutions, with attention to scalability, reliability, and business value realization in a fast-moving environment.

Qualifications

• Experience defining and driving enterprise GenAI strategy.
• Experience establishing AI governance and engineering standards.
• Experience leading enterprise-scale AI architecture using cloud platforms such as Bedrock, Azure OpenAI, or similar.

Responsibilities

• Define and drive enterprise Generative AI strategy aligned with organizational objectives, innovation goals, and AI transformation initiatives.
• Establish AI engineering standards, governance frameworks, and best practices for enterprise AI solution delivery.
• Lead the design of enterprise-scale AI architecture using cloud platforms (Bedrock, Azure OpenAI Service, Azure AI Foundry) and related tools.
• Define enterprise standards for Retrieval-Augmented Generation (RAG), Graph RAG, Agentic AI systems, and intelligent automation architectures.
• Drive adoption of AI agents, tool-calling frameworks, and autonomous workflow solutions across business functions.
• Drive adoption of enterprise multi-agent architectures, HITL governance, and scalable AI engineering patterns.
• Establish governance standards for model customization, fine-tuning, prompt engineering, retrieval quality, and AI solution lifecycle management.
• Define architecture patterns and engineering standards using LangChain, LangGraph, and related frameworks.

Skills

Agentic AI Systems

GenAI Framework Concepts

Cloud Application Integration

AI Search Index

AI Agents Tool Calling

LangChain

LangGraph

Tools

LangChain

LangGraph

AI Search Index

Agentic AI Tooling

Job description

Gen AI Fullstack - Lead

Location: Noida

Mandatory Skills

• Agentic AI Systems
• Advanced GenAI Agentic Framework Concepts
• Cloud Application Integration Deployment
• AI Search Index
• AI Agents Tool Calling
• LangChain
• LangGraph

Key Responsibilities

• Define and drive enterprise Generative AI strategy aligned with organizational objectives, innovation goals, and AI transformation initiatives.
• Establish AI engineering standards, governance frameworks, and best practices for enterprise AI solution delivery.
• Lead the design of enterprise-scale AI architecture using Amazon Bedrock, Azure OpenAI Service, Azure AI Foundry, Grog, or AI Search Index platforms.
• Define enterprise standards for Retrieval-Augmented Generation (RAG), Graph RAG, Agentic AI systems, and intelligent automation architectures.
• Drive adoption of AI agents, tool-calling frameworks, and autonomous workflow solutions across business functions.
• Drive adoption of enterprise multi-agent architectures, Human-in-the-Loop (HITL) governance, and scalable AI engineering patterns supporting secure and reliable business automation.
• Establish governance standards for model customization, fine-tuning, prompt engineering, retrieval quality, and AI solution lifecycle management.
• Define enterprise standards for prompt engineering pipelines, vector databases, semantic search, Retrieval-Augmented Generation, Model Context Protocol (MCP), and AI agent orchestration frameworks.
• Define architecture patterns and engineering standards using LangChain, LangGraph, and related workflow orchestration frameworks.
• Establish enterprise AI engineering standards covering secure API design, authentication, authorization, asynchronous processing, scheduling, scalability, deployment, observability, and operational resilience.
• Establish cloud integration and deployment standards for scalable and secure AI-enabled applications.
• Establish enterprise integration standards supporting databases, enterprise APIs, messaging platforms, and cloud-native AI application deployment.
• Lead architecture reviews and ensure AI solutions meet scalability, reliability, maintainability, explainability, and business value objectives.
• Guide teams on GenAI architecture, agentic systems, AI governance, and enterprise AI adoption best practices.
• Identify AI-related risks, governance gaps, operational challenges, and architectural limitations while defining mitigation strategies.
• Collaborate with various teams and leadership stakeholders to align AI initiatives with organizational objectives.
• Drive continuous improvement initiatives focused on AI maturity, innovation, operational effectiveness, governance, and business value realization.

Behavioral Competencies

• Demonstrates leadership and accountability in driving AI engineering excellence across programs and initiatives.
• Collaborate effectively with various teams and business stakeholders to ensure smooth delivery.
• Promotes a culture of innovation, responsible AI adoption, quality, and continuous improvement.