Join Iris Software, a rapidly growing IT services company recognized among India's Top 25 Best Workplaces in IT. We are seeking a Generative AI Engineer passionate about building cutting-edge AI-powered applications. At Iris, we foster a culture that values talent, ambition, and provides a launchpad for your career growth.

Our vision is to be a trusted technology partner, empowering clients across financial services, healthcare, transportation, and professional services with innovative solutions. We work with advanced technologies including Data & Analytics, Cloud, DevOps, and MLOps. "Build Your Future. Own Your Journey." is our Employee Value Proposition, reflecting our commitment to your career development and impact.

This role offers opportunities to work on complex, mission-critical applications, engage in personalized career development, continuous learning, and mentorship. We encourage you to explore your potential and grow both personally and professionally within our dynamic environment. Discover more about our culture through our "inside look" video.

Key responsibilities include designing and implementing Generative AI applications, translating requirements into efficient Python services, and working with LLM orchestration frameworks like LangChain and custom agents. You will contribute to proof-of-concepts and explore new GenAI capabilities.

You will also build and enhance RAG pipelines using embeddings and vector databases, implement basic Agentic workflows under senior guidance, and work with vector search systems. Optimizing indexing and retrieval, along with exposure to MCP/tool-integration frameworks, will be part of your role. Collaboration is key; you will participate in code reviews, design discussions, and documentation, adhering to best practices in coding, testing, and DevOps.

We are looking for a candidate with strong hands-on proficiency in Python, including Flask, REST, and async programming. Practical experience with Generative AI, LLM-based applications, and a good understanding of RAG systems, embeddings, and vector databases are essential.

Familiarity with Agentic frameworks such as LangChain, LangGraph, ReAct, or OpenAI Assistants is required. You should also have experience with AWS Cloud services (ECS, S3, API Gateway, IAM, Bedrock), API development, microservices, and containerization. Knowledge of CI/CD pipelines, Docker, and GitLab/GitHub Actions is also expected.