Shape your career at Iris Software, recognized as one of India's Top 25 Best Workplaces in the IT industry. Join an award-winning culture that values your talent and ambition, and become part of a fast-growing IT services company where you own your success story.

Iris Software aims to be the most trusted technology partner for its clients and the preferred choice for top industry professionals. With over 4,300 associates across India, USA, and Canada, we empower enterprise clients in financial services, healthcare, transportation & logistics, and professional services through technology-enabled transformation. Our work involves complex, mission-critical applications utilizing cutting-edge technologies in Application & Product Engineering, Data & Analytics, Cloud, DevOps, Data & MLOps, Quality Engineering, and Business Automation.

Define and lead enterprise Generative AI strategy, aligning with organizational objectives and innovation goals. Establish AI engineering standards, governance frameworks, and best practices for AI solution delivery.

Design enterprise-scale AI architecture using platforms like Amazon Bedrock, Azure OpenAI Service, or AI Search Index. Define standards for Retrieval-Augmented Generation (RAG), Agentic AI systems, and intelligent automation.

Drive the adoption of AI agents, tool-calling frameworks, and autonomous workflows. Implement multi-agent architectures and Human-in-the-Loop (HITL) governance for secure business automation.

Establish governance for model customization, fine-tuning, prompt engineering, and AI solution lifecycle management. Define standards for prompt engineering pipelines, vector databases, and AI agent orchestration frameworks using tools like LangChain and LangGraph.

Set enterprise AI engineering standards for secure API design, scalability, deployment, observability, and operational resilience. Ensure cloud integration and deployment standards support scalable and secure AI-enabled applications.

Lead architecture reviews to ensure AI solutions meet objectives for scalability, reliability, maintainability, and business value. Guide teams on GenAI architecture, agentic systems, and enterprise AI adoption best practices.

Identify AI-related risks, governance gaps, and architectural limitations, defining mitigation strategies. Collaborate with stakeholders to align AI initiatives with organizational goals and drive continuous improvement in AI maturity, innovation, and operational effectiveness.

We are seeking skilled engineers with a strong foundation in Generative AI and agentic systems. A deep understanding of cloud application integration and deployment is essential.

Key mandatory skills include Agentic AI Systems, Advanced GenAI & Agentic Framework Concepts, Cloud Application Integration & Deployment, AI Search Index, LangChain, and AI Agents & Tool Calling. Familiarity with platforms such as Amazon Bedrock, Azure OpenAI Service, Azure AI Foundry, and Grog is also required.

Experience in defining enterprise AI strategies and establishing engineering standards is crucial. Candidates should be adept at designing AI architectures and defining standards for RAG, Graph RAG, and intelligent automation. The role involves driving the adoption of AI agents and multi-agent architectures.

Proficiency in prompt engineering, vector databases, semantic search, and AI agent orchestration frameworks like LangChain and LangGraph is expected. Strong knowledge of secure API design, scalability, observability, and operational resilience is also necessary.

Behavioral competencies should include leadership, accountability, and effective collaboration with teams and business stakeholders to ensure smooth project delivery. An innovative mindset and a commitment to driving AI engineering excellence are highly valued.