Job Details Role / Job Title: AI Engineers Work Location: Redhill Mode of Working: Hybrid Office Attendance (Hybrid): 3 days The Role The AI Engineer will spearhead AI-driven innovation across insurance, annuities, and retirement solutions, focusing on risk modeling, claims automation, fraud detection, customer engagement, and personalized retirement planning. This role ensures the development and deployment of AI solutions that improve operational efficiency, regulatory compliance, and customer trust while leveraging advanced analytics and automation. Your Responsibilities Design, develop, and optimize RAG-based solutions integrating retrieval systems with large language models. Build and maintain applications using LangChain to orchestrate complex AI workflows. Implement and manage vector databases (e.g., FAISS, Pinecone, Weaviate, Milvus) for fast similarity search and retrieval. Develop embedding pipelines for unstructured data using models like Sentence Transformers, OpenAI, or Hugging Face. Collaborate with data scientists and software engineers to create scalable AI-powered applications. Fine-tune and evaluate large language models for specific use cases and domain adaptation. Optimize retrieval and generation workflows for performance, accuracy, and cost-efficiency. Stay updated on the latest advancements in generative AI, retrieval techniques, and vector search technology. Collaborate with cross-functional teams to integrate AI models into products. Stay updated with the latest advancements in AI and machine learning technologies. Conduct research to improve existing AI systems and develop new approaches. Knowledge of NLP, computer vision, or reinforcement learning. Experience deploying AI models in production environments. Your Profile Essential Skills / Knowledge / Experience Proven experience in AI, machine learning, or deep learning. Proficiency in programming languages such as Python, R, or Java. Experience with AI frameworks like TensorFlow, PyTorch, or Keras. Experience with large language models (GPT, BERT, etc.). Fine-tuning and prompt engineering. Experience with vector similarity search. Knowledge of popular vector DBs: Pinecone, Weaviate, FAISS, Vespa, Milvus. Generating and managing embeddings (using models like SentenceTransformers, OpenAI, Hugging Face). Familiarity with LangChain for building LLM-powered applications. Ability to create chains, prompts, and agents. Desirable Skills / Knowledge / Experience Experience with data ingestion, indexing, and querying. Working with unstructured data (text, documents, images).