Join a recognized Top 25 Best Workplace in India's IT industry and contribute to cutting-edge Generative AI solutions. Iris Software is a rapidly growing IT services company committed to being a trusted technology partner and a top choice for professionals seeking to realize their full potential. With a global presence across India, the USA, and Canada, we empower enterprise clients in financial services, healthcare, transportation, and professional services through technology-enabled transformation. Our expertise spans complex application engineering, data and analytics, cloud, DevOps, MLOps, quality engineering, and business automation.

At Iris, your career is a journey of ownership and growth. We foster an environment where talent is valued, contributions have impact, and continuous learning is encouraged. Experience working on advanced projects, benefit from personalized career development, and thrive in a culture that supports both professional and personal advancement.

Architect and develop advanced enterprise Generative AI solutions using platforms like Amazon Bedrock and Azure AI Foundry. Define robust AI solution architectures and implementation strategies aligned with business objectives.

Implement cutting-edge AI patterns including Retrieval-Augmented Generation (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, exploring emerging tools such as AutoGen or CrewAI. Optimize prompt strategies, retrieval mechanisms, and response generation for superior performance.

Design and implement prompt engineering pipelines, integrating vector databases and semantic search for scalable AI applications. Develop workflows using LangChain or LangGraph for efficient AI application development.

Establish scalable AI engineering architectures incorporating best practices for authentication, authorization, asynchronous processing, API governance, and enterprise deployment. Lead model fine-tuning and customization initiatives to enhance domain-specific AI capabilities.

Define and implement cloud-native AI integration patterns for enterprise ecosystems, supporting APIs, databases, and event-driven architectures. Create evaluation frameworks to ensure AI response quality, reliability, and relevance.

Design Human-in-the-Loop (HITL) workflows for AI quality improvement and governance. Review AI solution designs to uphold engineering standards, scalability, maintainability, and responsible AI practices.

Troubleshoot complex AI workflow challenges through detailed root cause analysis. Mentor team members on GenAI frameworks, RAG, agentic systems, and AI engineering best practices. Drive continuous improvement in AI solution quality and operational effectiveness.

Demonstrated expertise in Advanced GenAI and Agentic Framework Concepts is essential. Proficiency in Cloud Application Integration and Deployment, AI Agents, Tool Calling, Azure AI Foundry, Agentic AI Systems, LangChain, and LangGraph is required.

Mandatory competencies include a strong understanding of DevOps/Configuration Management (GitLab, GitHub, Bitbucket), UI (React), and Cloud technologies (Azure DevOps, Azure Pipelines, Azure CLI). Expertise in GenAI, specifically Prompt Engineering, Vector Databases, Workflow & Agentic Frameworks, Fine-tuning & Model Customization, AI Agents & Tool Calling, RAG/Graph RAG/Agentic AI Systems, Python, Pandas, and NumPy is critical.

An ability to integrate cloud applications and deploy them effectively is necessary. Excellent communication and collaboration skills are vital for working within a team and across departments. Experience with mandatory skills ensures a strong foundation for building and deploying sophisticated AI solutions.