Join Iris Software, a rapidly growing IT services company recognized among India's Top 25 Best Workplaces in the IT industry. We are dedicated to being a trusted technology partner and empowering top professionals to achieve their full potential. With a global presence and a focus on cutting-edge technologies, Iris fosters a culture of ownership, innovation, and continuous growth for its over 4,300 associates.

We specialize in application and product engineering, data & analytics, cloud, DevOps, MLOps, quality engineering, and business automation, working on complex, mission-critical applications. At Iris, your career journey is a launchpad, where your voice matters and your work creates real impact through personalized development, mentorship, and exposure to advanced projects.

Spearhead the design and development of enterprise-grade Generative AI solutions utilizing platforms like Amazon Bedrock, Azure OpenAI Service, and Azure AI Foundry. Architect AI solutions that align with both business objectives and technical requirements.

Lead the implementation of Retrieval-Augmented Generation (RAG), Graph RAG, and Agentic AI architectures for diverse enterprise use cases. Develop intelligent AI agents, tool-calling workflows, and autonomous task execution frameworks, utilizing frameworks like LangGraph and exploring emerging options such as AutoGen or CrewAI.

Optimize prompt strategies, retrieval mechanisms, context orchestration, and response generation. Design and implement prompt engineering pipelines, vector database integrations, and semantic search solutions. Develop scalable AI engineering architectures incorporating authentication, authorization, asynchronous processing, and API governance.

Drive fine-tuning and model customization initiatives to enhance domain-specific AI performance. Define robust AI integration patterns and deployment approaches for enterprise application ecosystems, including cloud-native patterns for APIs, databases, and event-driven architectures. Establish comprehensive evaluation frameworks for AI response quality, reliability, and consistency, including Human-in-the-Loop (HITL) workflows.

Review AI solution designs to ensure adherence to engineering standards, scalability, and responsible AI practices. Troubleshoot complex AI workflow and model behavior challenges through detailed root cause analysis. Mentor team members on GenAI frameworks, RAG architectures, and AI engineering best practices, fostering continuous improvement and innovation.

Proven expertise in Retrieval-Augmented Generation (RAG), Advanced Generative AI, and Agentic Framework Concepts. Strong proficiency in Cloud Application Integration and Deployment, Agentic AI Systems, Azure AI Foundry, and Azure OpenAI Service.

Skilled in AI Agents, Tool Calling, LangChain, and LangGraph. Experience in designing and implementing multi-agent orchestration solutions. Ability to design and optimize prompt strategies, retrieval mechanisms, and response generation frameworks.

Experience with prompt engineering pipelines, vector database integration, semantic search solutions, and RAG architectures. Design of scalable AI engineering architectures, including authentication, authorization, asynchronous processing, and API governance. Familiarity with fine-tuning and model customization for improved AI performance.

Ability to define AI integration patterns and deployment approaches for enterprise applications. Design of cloud-native AI integration patterns supporting APIs, databases, and event-driven architectures. Establishment of evaluation frameworks for AI quality and reliability, including HITL workflows.

Demonstrated ability to review AI solution designs for adherence to standards, scalability, and responsible AI practices. Capable of troubleshooting complex AI workflow challenges through root cause analysis. Strong ownership, effective collaboration with diverse teams, and a proactive approach to innovation and quality-focused engineering are essential.