Join Iris Software, a rapidly growing IT services company and one of India’s Top 25 Best Workplaces in the IT industry. We are recognized for our award-winning culture that values talent and ambition, empowering employees to shape their own success stories. Our vision is to be the most trusted technology partner for our enterprise clients, fostering their transformation across various sectors like financial services, healthcare, transportation, and professional services.

At Iris, every role is a launchpad for growth, guided by our Employee Value Proposition: “Build Your Future. Own Your Journey.” We cultivate an environment where potential is recognized, voices are heard, and work creates tangible impact. Through cutting-edge projects, personalized career development, continuous learning, and mentorship, we support your professional and personal evolution.

Lead the design, architecture, and development of scalable Generative AI solutions, including applications leveraging RAG (Retrieval Augmented Generation) and agentic workflows. Drive the adoption of LLM orchestration frameworks like LangChain and OpenAI tools.

Develop RAG pipelines utilizing vector databases and embeddings, implement agentic workflows, and optimize retrieval mechanisms. Build robust backend services, API layers, and model-serving components in Python, with a strong focus on performance and security.

Mentor a team of engineers, conduct code and design reviews, and collaborate effectively with cross-functional teams including Product, Architecture, and Security. Ensure adherence to best practices in coding, testing, observability, and DevOps.

This role requires 8-10 years of experience with strong expertise in Python, AWS Cloud, and Generative AI. Significant hands-on experience with RAG, agentic workflows, and building LLM-powered applications is essential.

Proficiency in Python (Flask, REST, async programming) is mandatory. You should possess deep knowledge of Generative AI concepts, LLM applications, and RAG development, including vector databases and embeddings. Experience with agent frameworks such as LangChain, LangGraph, or OpenAI Assistants is required.

A solid understanding of cloud architectures (AWS preferred) is necessary, along with experience in API development, microservices, and event-driven systems. Familiarity with CI/CD pipelines, Docker, and version control systems like GitLab or GitHub Actions is also expected.