Opportunity to lead the design and implementation of cutting-edge Generative AI solutions within enterprise environments. This role demands deep expertise in LLMs, RAG, vector databases, and agentic AI frameworks, complemented by proficiency in cloud-native deployments and CI/CD automation. You will be instrumental in bridging business needs with advanced AI capabilities, collaborating closely with stakeholders across data science, ML, and engineering teams to deliver robust, scalable, and secure GenAI platforms.

Join a dynamic team at Iris Software, recognized as one of India's Top 25 Best Workplaces in IT. Shape your career in an award-winning culture that values talent and ambition. We empower our professionals to own their journey and build their future.

Architect and design comprehensive GenAI solutions, including RAG pipelines, agentic workflows, and multimodal use cases. Translate complex business challenges into actionable GenAI-driven use cases, outlining clear solution blueprints and implementation roadmaps. Develop and refine retrieval systems using embeddings, chunking strategies, and evaluation metrics. Integrate and optimize vector databases for performance and relevance. Build sophisticated agentic systems leveraging frameworks like LangChain and LangGraph. Define scalable and secure cloud architecture patterns for GenAI deployments. Drive productionization through robust CI/CD pipelines and containerization best practices. Uphold responsible AI principles, ensuring security, governance, privacy, and compliance. Provide technical leadership, mentorship, and best-practice guidance to engineering teams, fostering alignment with project timelines and business objectives.

Requires strong hands-on and architectural expertise in LLMs, RAG, vector databases, and agentic AI frameworks. Must possess experience in cloud-native deployments and CI/CD automation. Key technical skills include GenAI/LLM Architecture & Algorithms, Vector Databases & Retrieval Systems (e.g., Pinecone, FAISS), Agentic AI Frameworks (e.g., LangChain, LangGraph), Cloud Architecture & Deployments (GCP preferred), and CI/CD & Productionization (Docker, Kubernetes).

Mandatory competencies include Data Science and Machine Learning - Gen AI, Development Tools and Management - CI/CD, and Cloud - GCP - API Management. A background in Data Science and Machine Learning with a focus on Generative AI is essential. Excellent communication skills are also required.