Join Iris Software, a rapidly growing IT services company recognized among India's Top 25 Best Workplaces in IT. We are seeking a Senior Engineer with expertise in Generative AI and Fullstack development to drive our AI transformation initiatives. At Iris, we empower our associates to own their career journeys and achieve professional growth in an award-winning culture.

Our vision is to be a leading technology partner for enterprise clients, fostering innovation across financial services, healthcare, transportation, and professional services. We specialize in complex, mission-critical applications utilizing cutting-edge technologies in Application & Product Engineering, Data & Analytics, Cloud, DevOps, MLOps, Quality Engineering, and Business Automation.

Define and implement enterprise Generative AI strategies, ensuring alignment with business objectives and AI transformation goals. Establish robust AI engineering standards, governance frameworks, and best practices for solution delivery. Design enterprise-scale AI architectures using platforms like Amazon Bedrock, Azure OpenAI Service, and AI Search Index.

Develop enterprise standards for Retrieval-Augmented Generation (RAG), Graph RAG, AI Agents, and intelligent automation. Drive the adoption of multi-agent architectures, Human-in-the-Loop (HITL) governance, and scalable AI engineering patterns. Establish governance for model customization, fine-tuning, prompt engineering, and AI solution lifecycle management.

Define architecture patterns and engineering standards for prompt engineering pipelines, vector databases, semantic search, and AI agent orchestration using frameworks like LangChain and LangGraph. Ensure secure API design, authentication, authorization, asynchronous processing, scalability, observability, and operational resilience in AI-enabled applications. Lead architecture reviews to ensure AI solutions meet scalability, reliability, and business value objectives. Guide teams on GenAI architecture, agentic systems, and AI governance best practices. Identify and mitigate AI-related risks and architectural limitations.

Proven experience in defining and driving enterprise Generative AI strategy and architecture.

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

Experience with AI platforms such as Amazon Bedrock, Azure OpenAI Service, Azure AI Foundry, or Grog is essential. Expertise in Retrieval-Augmented Generation (RAG), Graph RAG, and intelligent automation architectures is required.

Familiarity with prompt engineering pipelines, vector databases, semantic search, Model Context Protocol (MCP), and AI agent orchestration frameworks is necessary. Knowledge of LangChain and LangGraph for workflow orchestration is key.

Strong understanding of enterprise AI engineering standards covering secure API design, authentication, authorization, asynchronous processing, scalability, deployment, observability, and operational resilience.

Demonstrated leadership and accountability in driving AI engineering excellence and collaborating effectively with diverse teams and stakeholders to ensure smooth delivery.