Join Iris Software, recognized among India's Top 25 Best Workplaces in the IT industry, and contribute to a dynamic, award-winning culture. We are a fast-growing IT services company committed to enabling clients' digital transformation across diverse sectors like financial services, healthcare, and logistics.

Our expertise spans complex application engineering, data analytics, cloud, DevOps, and MLOps. At Iris, your career journey is a launchpad for growth, guided by our philosophy "Build Your Future. Own Your Journey." We foster an environment that values your potential, amplifies your voice, and ensures your work makes a significant impact through cutting-edge projects, personalized development, and continuous mentorship.

Lead the definition and execution of enterprise Generative AI strategies, aligning with organizational objectives and innovation goals.

Establish robust AI engineering standards, governance frameworks, and best practices for delivering enterprise-scale AI solutions.

Architect enterprise AI solutions leveraging platforms such as Amazon Bedrock, Azure OpenAI Service, Azure AI Foundry, Grog, or AI Search Index.

Define standards for Retrieval-Augmented Generation (RAG), Graph RAG, agentic AI systems, and intelligent automation architectures.

Drive the adoption of AI agents, tool-calling frameworks, and autonomous workflow solutions across business functions.

Spearhead the implementation of enterprise multi-agent architectures, Human-in-the-Loop (HITL) governance, and scalable AI engineering patterns for secure business automation.

Establish governance for model customization, fine-tuning, prompt engineering, retrieval quality, and AI solution lifecycle management.

Define standards for prompt engineering pipelines, vector databases, semantic search, Model Context Protocol (MCP), and AI agent orchestration frameworks.

Develop architecture patterns and engineering standards using LangChain, LangGraph, and related workflow orchestration tools.

Ensure adherence to enterprise AI engineering standards for secure API design, authentication, authorization, asynchronous processing, scheduling, scalability, deployment, observability, and operational resilience.

Set 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.

Mentor teams on GenAI architecture, agentic systems, AI governance, and best practices for enterprise AI adoption.

Identify and mitigate AI-related risks, governance gaps, operational challenges, and architectural limitations.

Collaborate with various teams and leadership to align AI initiatives with organizational goals.

Drive continuous improvement in AI maturity, innovation, operational effectiveness, governance, and business value realization.

Demonstrate strong leadership and accountability in driving AI engineering excellence across programs and initiatives.

Collaborate effectively with diverse teams and business stakeholders to ensure seamless project delivery.

Champion a culture of innovation, responsible AI adoption, quality, and continuous improvement.

Mandatory skills include expertise in Agentic AI Systems, Advanced GenAI & Agentic Framework Concepts, Cloud Application Integration & Deployment, AI Search Index, AI Agents & Tool Calling, LangChain, and LangGraph.

Experience with Amazon Bedrock, Azure OpenAI Service, Azure AI Foundry, Grog, or AI Search Index platforms is essential.

Proficiency in defining enterprise standards for Retrieval-Augmented Generation (RAG), Graph RAG, agentic AI systems, and intelligent automation architectures is required.

Knowledge of prompt engineering pipelines, vector databases, semantic search, Model Context Protocol (MCP), and AI agent orchestration frameworks is critical.