Join Iris Software, a recognized leader among India's top IT workplaces, and shape your career in an award-winning culture. We are a fast-growing IT services company committed to being our clients' most trusted technology partner. With a global team, we empower enterprise clients with cutting-edge solutions in financial services, healthcare, transportation, and professional services.

Our focus spans complex application engineering, data and analytics, cloud, DevOps, MLOps, quality engineering, and business automation. At Iris, every role is a stepping stone for growth, driven by our philosophy 'Build Your Future. Own Your Journey.' We foster an environment where your potential is valued, your voice is heard, and your work makes a tangible impact. Through challenging projects, personalized career development, continuous learning, and mentorship, we support your professional and personal evolution.

As a Lead Fullstack Gen AI professional, you will define and execute the enterprise Generative AI strategy, aligning it with organizational goals and AI transformation objectives. You will establish robust AI engineering standards, governance frameworks, and best practices for delivering enterprise-scale AI solutions.

Key responsibilities include designing AI architecture using platforms like Amazon Bedrock or Azure OpenAI Service, and defining enterprise standards for RAG, Graph RAG, agentic AI systems, and intelligent automation. You will drive the adoption of AI agents, tool-calling frameworks, autonomous workflows, and multi-agent architectures, ensuring Human-in-the-Loop governance and scalable engineering patterns.

Further, you will establish governance for model customization, fine-tuning, prompt engineering, retrieval quality, and AI solution lifecycle management. This includes defining standards for prompt engineering pipelines, vector databases, semantic search, Model Context Protocol (MCP), and agent orchestration frameworks using LangChain and LangGraph. You will also define enterprise AI engineering standards covering secure API design, asynchronous processing, scalability, deployment, observability, and operational resilience, along with cloud integration standards for AI-enabled applications and enterprise systems.

We are seeking a seasoned professional with mandatory expertise in Agentic AI Systems, Advanced GenAI & Agentic Framework Concepts, Cloud Application Integration & Deployment, LangChain, LangGraph, AI Search Index, and AI Agents & Tool Calling. Proficiency in Python and Terraform is also required.

Key competencies include demonstrating leadership and accountability in driving AI engineering excellence, collaborating effectively with diverse teams and stakeholders, and fostering a culture of innovation and responsible AI adoption. You should apply strategic thinking to address AI risks, architectural challenges, and governance requirements, making strong decisions that balance innovation, scalability, reliability, governance, and business objectives.

Effective communication regarding AI strategy, risks, dependencies, solution outcomes, and business value is essential. You will also be responsible for conducting architecture reviews, ensuring AI solutions meet objectives for scalability, reliability, maintainability, explainability, and business value, while guiding teams on GenAI architecture and adoption best practices.