Gen AI Fullstack - Engineer

Iris Software, Inc.; Dadri; On-site; INR 1,500,000 - 1,900,000; Full time

Job summary

Iris Software, Inc. is seeking a GenAI Fullstack Engineer to design and drive enterprise AI architectures, leveraging agentic systems and scalable AI patterns.

You will collaborate with cross-functional teams to establish governance, implement LangChain-based workflows, and accelerate AI transformation initiatives across the organization.

Strong communication and leadership are expected as you guide teams through architecture reviews and adoption of multi-agent solutions.

Qualifications

• Experience designing GenAI systems and agentic architectures.
• Familiarity with LangChain and AI agent tool-calling.
• Experience with enterprise AI integration and cloud deployment.

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 available cloud and AI platforms.
• Define enterprise standards for Retrieval-Augmented Generation (RAG) and intelligent automation architectures.
• Drive adoption of AI agents, tool-calling frameworks, and autonomous workflows across business functions.
• Drive adoption of enterprise multi-agent architectures and HITL governance for secure automation.
• Establish governance standards for model customization, fine-tuning, and prompt engineering.
• Define enterprise standards for prompt pipelines, vector stores, semantic search, and MCP.
• Define architecture patterns using LangChain and related orchestration frameworks.
• Establish enterprise AI engineering standards covering secure API design, authentication, asynchronous processing, and observability.
• Establish cloud integration and deployment standards for scalable AI-enabled applications.
• Establish enterprise integration standards for databases, APIs, and messaging platforms.
• Lead architecture reviews to ensure scalability and business value.
• Guide teams on GenAI architecture, governance, and enterprise adoption best practices.
• Identify AI-related risks and mitigation strategies.
• Collaborate with leadership to align AI initiatives with objectives.
• Drive continuous improvement in AI maturity and value.

Skills

Agentic AI Systems

GenAI Architectures

Cloud Application Deployment

AI Search Index

LangChain

Agenting Tool Calling

Job description

Gen AI Fullstack - Engineer

Location: Noida, UP, India

Job Description

Mandatory Skills

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

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.