Iris Software is seeking a highly skilled Gen AI Fullstack Engineer to drive enterprise Generative AI strategy and implementation. Join a top-tier IT workplace recognized for its award-winning culture and commitment to employee growth. We are a fast-growing IT services company focused on transforming enterprises with cutting-edge technology solutions.

Our vision is to be a trusted technology partner, empowering clients across financial services, healthcare, transportation, and professional services. We work on complex, mission-critical applications leveraging the latest in AI, Data & Analytics, Cloud, and DevOps.

At Iris, we believe in "Build Your Future. Own Your Journey." Every role is a launchpad for growth, offering ownership, continuous learning, and mentorship. Discover an environment where your potential is valued, your voice matters, and your work creates real impact.

Define and execute enterprise Generative AI strategy aligned with organizational goals and innovation objectives. Establish robust AI engineering standards, governance frameworks, and best practices for scalable AI solution delivery. Lead the architecture design for enterprise-scale AI solutions utilizing platforms like Amazon Bedrock, Azure OpenAI Service, 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 business functions. Implement enterprise multi-agent architectures, Human-in-the-Loop (HITL) governance, and scalable AI engineering patterns. Define governance standards for model customization, fine-tuning, prompt engineering, and AI solution lifecycle management. Establish standards for prompt engineering pipelines, vector databases, semantic search, and AI agent orchestration frameworks using LangChain and LangGraph. Ensure secure API design, authentication, authorization, asynchronous processing, scalability, deployment, and operational resilience for AI-enabled applications. Establish cloud integration and deployment standards for scalable and secure AI applications. Lead architecture reviews to ensure AI solutions meet objectives for scalability, reliability, maintainability, and business value. Guide teams on GenAI architecture, agentic systems, AI governance, and best practices for enterprise AI adoption. Identify and mitigate AI-related risks, governance gaps, and architectural limitations.

Deep expertise in Agentic AI Systems and advanced GenAI & Agentic Framework Concepts. Proficiency in Cloud Application Integration & Deployment, AI Search Index, and LangChain. Strong understanding of AI Agents & Tool Calling capabilities. Demonstrated leadership and accountability in driving AI engineering excellence. Ability to collaborate effectively with various teams and business stakeholders for seamless delivery. Experience in defining and driving enterprise AI strategies and governance frameworks. Proven ability to design enterprise-scale AI architectures using cloud platforms. Knowledge of RAG, Graph RAG, and intelligent automation architectures. Experience with multi-agent architectures and Human-in-the-Loop (HITL) governance. Familiarity with prompt engineering pipelines, vector databases, and AI agent orchestration frameworks. Understanding of secure API design, authentication, authorization, and operational resilience for AI applications. Experience in guiding teams on GenAI architecture and enterprise AI adoption best practices.