About the Company: We are a technology-led healthcare solutions provider. We are driven by our purpose to enable healthcare organizations to be future-ready.

About the Role: We are a technology-led healthcare solutions provider. We are driven by our purpose to enable healthcare organizations to be future-ready. We offer accelerated, global growth opportunities for talent that’s bold, industrious, and nimble. With Indegene, you gain a unique career experience that celebrates entrepreneurship and is guided by passion, innovation, collaboration, and empathy. To explore exciting opportunities at the convergence of healthcare and technology, check out www.careers.indegene.com Looking to jump-start your career?

We understand how important the first few years of your career are, which create the foundation of your entire professional journey. At Indegene, we promise you a differentiated career experience. You will not only work at the exciting intersection of healthcare and technology but also will be mentored by some of the most brilliant minds in the industry. We are offering a global fast-track career where you can grow along with Indegene’s high-speed growth.

We are purpose-driven. We enable healthcare organizations to be future ready and our customer obsession is our driving force. We ensure that our customers achieve what they truly want. We are bold in our actions, nimble in our decision-making, and industrious in the way we work.

Key Responsibilities: Key Responsibilities: The position will be directly responsible for the following: • Drive innovation through state-of-the-art LLM integration and Retrieval-Augmented Generation (RAG) strategies using Dataiku and modern AI frameworks• Experience with LLM Mesh, RAG pipelines, vector databases, embeddings, prompt engineering, and integration• Build applications powered by LLMs (OpenAI, Claude, Mistral, etc.) using LangChain, LlamaIndex, and related GenAI frameworks. • Implement RAG pipelines with vector DBs (Pinecone, FAISS, pgvector, ChromaDB) for grounding LLM responses with internal knowledge • Develop multimodal AI solutions (text, audio, image) and build autonomous agents where relevant. • Continuously improve model reliability, relevance by tuning prompt flows • Deploy GenAI models on AWS/GCP/Azure using services like SageMaker, Bedrock, Vertex AI • Ideate and design innovative solution frameworks aligning to market trends and technological innovations. Translating healthcare clients' business needs into technical solutions meeting user needs and business goals• POC building, go to market strategy building by application of AI/Gen AI use cases wherever applicable. Integrate large language models (LLMs), computer vision, or other AI/ML techniques into business solutions.