AI Engineer - NLP

We are looking for an experienced AI / LLM Scientist to design, develop, and deploy advanced Generative AI and Large Language Model (LLM) solutions for enterprise-scale healthcare and life sciences applications. The ideal candidate should possess deep expertise in NLP, LLM fine-tuning, prompt engineering, Agentic AI frameworks, and scalable AI solution development. Key Responsibilities Design, build, and optimize Generative AI and LLM-based applications for healthcare and life sciences use cases. Fine-tune, evaluate, and deploy Large Language Models (LLMs) using enterprise datasets. Develop and implement NLP pipelines for text processing, summarization, semantic search, and conversational AI systems. Build and orchestrate Agentic AI workflows using frameworks such as LangChain, LangGraph, AutoGen, CrewAI, or similar technologies. Perform prompt engineering, prompt optimization, and response evaluation for high-quality AI outputs. Work on Retrieval-Augmented Generation (RAG) architectures and vector database integrations. Collaborate with cross-functional teams including Data Engineering, Product, and Business stakeholders to deliver scalable AI solutions. Develop APIs, microservices, and AI integrations using Python and Java. Work with structured and unstructured data using SQL and modern database technologies. Conduct model experimentation, performance optimization, and AI solution validation. Stay updated with the latest advancements in Generative AI, Agentic AI, LLMOps, and foundation models. Required Skills 10+ years of overall IT experience with strong AI/ML exposure. Strong experience in Natural Language Processing (NLP) and Generative AI technologies. Hands-on expertise in Fine-Tuning LLMs and Prompt Engineering. Experience with Agentic AI frameworks such as LangChain, LangGraph, CrewAI, AutoGen, or equivalent. Strong programming skills in Python and Java. Good understanding of SQL and database concepts. Experience with AI/ML frameworks such as PyTorch, TensorFlow, Hugging Face Transformers, etc. Knowledge of RAG pipelines, vector databases, embeddings, and semantic search. Exposure to cloud platforms such as AWS, Azure, or GCP. Strong analytical, communication, and problem-solving skills. Preferred Qualifications Degree in Computer Science, Data Science, Artificial Intelligence, or related field. Experience working in Healthcare, Pharma, Life Sciences, or Clinical domains is highly preferred. Familiarity with Azure OpenAI, Databricks, Neo4j, ChromaDB, Pinecone, or similar tools is an added advantage. Experience in scalable AI deployment and MLOps practices is preferred. (ref:hirist.tech)