Join Iris Software, recognized as one of India's Top 25 Best Workplaces in the IT industry, and advance your career in a dynamic, award-winning culture. We are a fast-growing IT services company committed to being a trusted technology partner and empowering top professionals.

Our vision is to help enterprise clients thrive through technology-enabled transformation across various sectors, including financial services, healthcare, and logistics. We specialize in complex, mission-critical applications leveraging cutting-edge technologies like Data & Analytics, Cloud, DevOps, MLOps, and Business Automation.

At Iris, every role is an opportunity for growth, guided by our philosophy, "Build Your Future. Own Your Journey." We foster an environment where your potential is recognized, your contributions have a real impact, and you receive support for personal and professional development through cutting-edge projects, personalized career paths, and continuous learning.

Design and develop advanced Generative AI solutions using platforms such as Amazon Bedrock and Azure OpenAI Service. Define AI solution architectures and implementation strategies aligned with business goals.

Implement sophisticated RAG, Graph RAG, and Agentic AI architectures. Lead the development of intelligent AI agents, tool-calling workflows, and autonomous task execution frameworks.

Orchestrate multi-agent systems using frameworks like LangGraph and explore emerging tools such as AutoGen. Optimize prompt strategies, retrieval mechanisms, and response generation pipelines.

Design and implement prompt engineering workflows, vector database integrations, and semantic search solutions. Develop scalable AI application architectures incorporating authentication, asynchronous processing, API governance, and deployment best practices.

Lead model fine-tuning initiatives and define AI integration patterns for enterprise ecosystems. Establish robust evaluation frameworks for AI quality, reliability, and consistency.

Design Human-in-the-Loop workflows for AI improvement and governance. Review AI solution designs for adherence to standards, scalability, and responsible AI practices. Troubleshoot complex AI challenges through detailed root cause analysis.

Mentor team members on GenAI, RAG, and agentic systems. Drive continuous improvement in AI solution quality and operational effectiveness.

Proven expertise in Advanced GenAI and Agentic Framework Concepts, Cloud Application Integration & Deployment, and Python programming. Strong command over Azure OpenAI Service, AI Agents & Tool Calling, and frameworks like LangChain is essential.

Experience with Retrieval-Augmented Generation (RAG), Graph RAG, and Agentic AI Systems is crucial. Proficiency in designing and implementing workflows using LangChain or LangGraph for scalable AI application development is required.

Familiarity with prompt engineering, vector databases, and semantic search solutions is necessary. Ability to design scalable AI engineering architectures incorporating authentication, asynchronous processing, and API governance is expected.

Experience in fine-tuning and model customization is a plus. The ability to establish evaluation frameworks for AI response quality and troubleshoot complex AI workflow challenges is important.

Strong behavioral competencies including ownership, collaboration, innovation, analytical thinking, adaptability, and effective communication are vital. A commitment to secure, scalable, and responsible AI engineering practices is expected.