Join Iris Software, a rapidly expanding IT services company recognized among India's Top 25 Best Workplaces in the IT industry. We are seeking a Senior Engineer with expertise in Generative AI and Fullstack development to contribute to cutting-edge projects. Our vision is to be the most trusted technology partner for our clients and a prime destination for top IT professionals.

At Iris, we empower our associates to shape their career journeys through ownership and ample growth opportunities. We foster a culture that values potential, encourages voices, and drives tangible impact. With a global presence across India, the U.S.A., and Canada, we serve enterprise clients in financial services, healthcare, transportation & logistics, and professional services, focusing on complex, mission-critical applications.

Define and implement enterprise-wide Generative AI strategies, ensuring alignment with organizational goals and AI transformation initiatives. Establish robust AI engineering standards, governance frameworks, and best practices for delivering enterprise-scale AI solutions. Lead the architectural design of AI solutions utilizing platforms such as Amazon Bedrock, Azure OpenAI Service, Azure AI Foundry, and AI Search Index. Develop enterprise standards for Retrieval-Augmented Generation (RAG), Graph RAG, Agentic AI systems, and intelligent automation. Champion the adoption of AI agents, tool-calling frameworks, and autonomous workflows across various business functions. Drive the implementation of multi-agent architectures, Human-in-the-Loop (HITL) governance, and scalable AI engineering patterns for secure business automation. Establish governance standards for model customization, fine-tuning, prompt engineering, retrieval quality, and AI solution lifecycle management. Define comprehensive standards for prompt engineering pipelines, vector databases, semantic search, RAG, Model Context Protocol (MCP), and AI agent orchestration frameworks. Create architecture patterns and engineering standards using LangChain, LangGraph, and other workflow orchestration tools. Implement enterprise AI engineering standards covering secure API design, authentication, authorization, asynchronous processing, scalability, deployment, observability, and operational resilience. Set up cloud integration and deployment standards for scalable and secure AI-enabled applications. Define enterprise integration standards for databases, enterprise APIs, messaging platforms, and cloud-native AI application deployment. Conduct architecture reviews to ensure AI solutions meet objectives for scalability, reliability, maintainability, explainability, and business value. Provide guidance to teams on GenAI architecture, agentic systems, AI governance, and enterprise AI adoption best practices. Identify and mitigate AI-related risks, governance gaps, operational challenges, and architectural limitations. Collaborate with diverse teams and leadership to align AI initiatives with organizational objectives. Champion continuous improvement in AI maturity, innovation, operational effectiveness, governance, and business value realization.

Proven experience in defining and driving enterprise Generative AI strategy and standards. Expertise in designing enterprise-scale AI architectures using cloud platforms like Amazon Bedrock, Azure OpenAI Service, Azure AI Foundry, or AI Search Index. Strong understanding of Retrieval-Augmented Generation (RAG), Graph RAG, Agentic AI systems, and intelligent automation. Proficiency with AI agents, tool-calling frameworks, and autonomous workflow solutions. Experience with multi-agent architectures, Human-in-the-Loop (HITL) governance, and scalable AI engineering patterns. Knowledge of governance standards for model customization, fine-tuning, prompt engineering, and AI solution lifecycle management. Familiarity with prompt engineering pipelines, vector databases, semantic search, Model Context Protocol (MCP), and AI agent orchestration frameworks. Experience with LangChain, LangGraph, and related workflow orchestration frameworks. Understanding of enterprise AI engineering standards, including secure API design, cloud integration, and deployment. Ability to lead architecture reviews and ensure solutions meet stringent quality and business objectives. Strong leadership and accountability in driving AI engineering excellence. Excellent collaboration skills with teams and business stakeholders. Mandatory skills include: Agentic AI Systems, Advanced GenAI & Agentic Framework Concepts, Cloud Application Integration & Deployment, AI Search Index, LangChain, AI Agents & Tool Calling.