Join Iris Software, a rapidly growing IT services company and a recognized top workplace in India. We are seeking a seasoned Senior Engineer to spearhead advancements in Generative AI. This role offers an exceptional opportunity to contribute to cutting-edge projects within an award-winning culture that champions employee growth and innovation. Our vision is to be the most trusted technology partner, empowering clients across financial services, healthcare, transportation, and professional services.

At Iris, we believe in "Build Your Future. Own Your Journey." We provide a dynamic environment where your potential is recognized, your contributions are impactful, and you have the autonomy to shape your career path. Benefit from continuous learning, mentorship, and challenging projects that foster both professional and personal development.

Design and implement sophisticated enterprise Generative AI solutions leveraging platforms like Amazon Bedrock, Azure OpenAI, and AI Search. Define robust AI solution architectures and implementation strategies, aligning with business and technical goals. Develop advanced RAG, Graph RAG, and Agentic AI architectures for complex enterprise use cases. Lead the creation of intelligent AI agents, tool-calling workflows, and autonomous task execution frameworks. Orchestrate multi-agent systems using frameworks such as LangGraph, evaluating new tools like AutoGen or CrewAI. Optimize prompt strategies, retrieval mechanisms, context orchestration, and response generation frameworks.

Implement prompt engineering pipelines, vector database integrations, and semantic search solutions. Design and deploy scalable AI engineering architectures incorporating best practices for authentication, authorization, asynchronous processing, API governance, and enterprise deployment. Drive model fine-tuning initiatives for enhanced domain-specific performance. Establish comprehensive evaluation frameworks for AI response quality, reliability, and consistency. Design and implement Human-in-the-Loop (HITL) workflows for continuous AI quality improvement. Review AI solution designs to ensure adherence to engineering standards, scalability, and responsible AI principles. Troubleshoot complex AI workflow and model behavior challenges through detailed root cause analysis. Mentor team members on GenAI frameworks, RAG architectures, agentic systems, and AI engineering best practices. Champion continuous improvement in AI solution quality, innovation, and operational effectiveness.

This role requires a minimum of 5 to 8 years of experience in Generative AI and related technologies. Essential skills include a deep understanding of Advanced GenAI & Agentic Framework Concepts, Cloud Application Integration & Deployment, Python, FastAPI, AI Search Index, AI Agents & Tool Calling, Retrieval-Augmented Generation (RAG), Agentic AI Systems, LangGraph, LangChain, Vector Databases, and Prompt Engineering.

Proven experience in designing and developing enterprise Generative AI solutions is critical. The ideal candidate will have expertise in defining AI solution architectures, implementing RAG and Agentic AI architectures, and leading the development of intelligent AI agents. Familiarity with multi-agent orchestration solutions using frameworks like LangGraph and evaluating emerging frameworks is expected. A strong ability to design and optimize prompt strategies, implement prompt engineering pipelines, and integrate vector databases is also necessary.

Candidates must demonstrate strong ownership, collaborate effectively with diverse teams, and promote innovation through proactive experimentation. Excellent analytical thinking is required to address complex AI challenges. Adaptability to evolving AI technologies and strong communication skills for presenting AI solution designs, risks, and opportunities are essential. Meticulous attention to detail across all aspects of AI architecture, implementation, testing, and deployment is paramount. The role also involves mentoring team members and driving continuous improvement in AI engineering practices.