5 of 5 LlamaIndex Jobs in the South East

solutions using LLMs (e.g. OpenAI, Llama, Mistral, Claude) and vector databases (Pinecone, Weaviate, FAISS, etc.) Practical experience with GenAI frameworks such as LangChain, LlamaIndex, and agentic frameworks like AutoGen, CrewAI, LangGraph Strong Python expertise with AI/ML frameworks (PyTorch, TensorFlow) and NLP libraries Experience deploying AI solutions ...

Hands-on experience with LLMs, RAG, vector databases, and GenAI frameworks Experience deploying solutions on cloud platforms (AWS, Azure, or GCP) Familiarity with LangChain, LlamaIndex, or agentic frameworks is highly valuable Strong grounding in software engineering best practices (testing, versioning, CI/CD, scalability) Mindset & Behaviours: Seek ownership, not just ...

Model Deployment: Flask, FastAPI, MLflow Model Serving: Triton Inference Server, Hugging Face Inference Endpoints API Integration: OpenAI, Anthropic, Cohere, Mistral APIs LLM Frameworks: LangChain, LlamaIndex for building LLM-powered applications Vector Databases: FAISS, Weaviate, Pinecone, Qdrant (Nice-to-Have) Retrieval-Augmented Generation (RAG): Experience building hybrid systems combining LLMs with ...

experience with AI Workbenches on major cloud platforms, such as Gemini Enterprise, Azure AI Agent Familiarity with GenAI frameworks and libraries like LangChain, LlamaIndex, or Hugging Face. A solid understanding of generative AI concepts, models, and frameworks. Knowledge of the wider commerce technology stack, including PXM, CMS, and CDP platforms. ...

What you’ll work on Building Agentic AI workflows and automation Designing RAG pipelines for insurance data Developing LLM-powered tools using Python , LangChain , LlamaIndex , and vector databases Evaluating, fine-tuning, and integrating LLMs (OpenAI/Anthropic/Mistral) Collaborating with Data Science & Engineering teams to productionise models What ...