21 of 21 LlamaIndex Jobs in the UK excluding London

applied to AI/ML systems - Semantic search, vector/embedding infrastructure, and RAG pipeline construction - LLM orchestration and agentic frameworks (eg LangChain/LlamaIndex-style tooling, multi-agent patterns) - Prompt engineering and systematic evaluation/guardrail tooling (hallucination detection, safety testing) - LLMOps/MLOps - model versioning, deployment, monitoring ...

ReAct‐style loops, state and checkpointing, retries and interrupts, human‐in‐the‐loop review gates. Frameworks: At least one of: Anthropic Agent SDK, LangGraph, LlamaIndex, or an equivalent orchestration framework, plus the judgement to know when to use none of them. RAG and retrieval: Chunking strategy, embeddings, hybrid and semantic ...

LangChain, AirFlow, etc Agentic AI and ML Integration of commercial and open-source LLMs into agentic workflows Agent and orchestration frameworks such as LangChain, LlamaIndex, Semantic Kernel, or CrewAI, with strong judgment about when to use frameworks versus building lighter-weight primitives Model-level work using PyTorch and the Hugging ...

experience with NoSQL databases Hands-on experience building NLP, LLM, RAG and agentic AI solutions using frameworks such as LangChain, LangGraph, LlamaIndex and Hugging Face Transformers Familiarity with MLOps practices including Git, CI/CD and model lifecycle management Experience with containerisation tools such as Docker and orchestration tools such ...

record with the AI Development Life Cycle (AI DLC). Modern AI stack depth: Python/TypeScript, PyTorch, an orchestration framework (LangGraph, LangChain/LlamaIndex, CrewAI, or AutoGen), and vector databases (Pinecone, Qdrant, Weaviate, or Milvus) Model‐serving infrastructure: For example Triton/vLLM as well as LLM gateway products ...

hands-on with emerging technologies – exploring what works, what scales, and what’s next:Experimenting with Generative AI frameworks and tools such as LangChain, LlamaIndex, Hugging Face, and APIs from OpenAI and Anthropic.Building retrieval-augmented generation (RAG) prototypes with vector stores and knowledge graphs.Developing and testing agentic architectures through ...

hands-on with emerging technologies – exploring what works, what scales, and what's next: Experimenting with Generative AI frameworks and tools such as LangChain, LlamaIndex, Hugging Face, and APIs from OpenAI and Anthropic. Building retrieval-augmented generation (RAG) prototypes with vector stores and knowledge graphs. Developing and testing agentic architectures ...

emerging LLM architectures.GenAI Frameworks & Platforms: Proficient with Data & AI platforms (Azure AI, Vertex AI, Databricks, Hugging Face), advanced GenAI frameworks (LangChain, HF Transformers, LlamaIndex) & Agentic architectures (LangGraph, SmolAgents, PydanticAI) Prompt Engineering: Deep prompt engineering & optimization skills for GenAI.Vector DBs & RAG: Designed solutions using vector DBs & Retrieval Augmented GenAI ...

emerging LLM architectures.GenAI Frameworks & Platforms: Proficient with Data & AI platforms (Azure AI, Vertex AI, Databricks, Hugging Face), advanced GenAI frameworks (LangChain, HF Transformers, LlamaIndex) & Agentic architectures (LangGraph, SmolAgents, PydanticAI) Prompt Engineering: Deep prompt engineering & optimization skills for GenAI.Vector DBs & RAG: Designed solutions using vector DBs & Retrieval Augmented GenAI ...

emerging LLM architectures.GenAI Frameworks & Platforms: Proficient with Data & AI platforms (Azure AI, Vertex AI, Databricks, Hugging Face), advanced GenAI frameworks (LangChain, HF Transformers, LlamaIndex) & Agentic architectures (LangGraph, SmolAgents, PydanticAI) Prompt Engineering: Deep prompt engineering & optimization skills for GenAI.Vector DBs & RAG: Designed solutions using vector DBs & Retrieval Augmented GenAI ...

emerging LLM architectures.GenAI Frameworks & Platforms: Proficient with Data & AI platforms (Azure AI, Vertex AI, Databricks, Hugging Face), advanced GenAI frameworks (LangChain, HF Transformers, LlamaIndex) & Agentic architectures (LangGraph, SmolAgents, PydanticAI) Prompt Engineering: Deep prompt engineering & optimization skills for GenAI.Vector DBs & RAG: Designed solutions using vector DBs & Retrieval Augmented GenAI ...

emerging LLM architectures.GenAI Frameworks & Platforms: Proficient with Data & AI platforms (Azure AI, Vertex AI, Databricks, Hugging Face), advanced GenAI frameworks (LangChain, HF Transformers, LlamaIndex) & Agentic architectures (LangGraph, SmolAgents, PydanticAI) Prompt Engineering: Deep prompt engineering & optimization skills for GenAI.Vector DBs & RAG: Designed solutions using vector DBs & Retrieval Augmented GenAI ...

executive stakeholders. Excellent problem-solving skills with the ability to navigate ambiguity and deliver pragmatic solutions. Nice to Have Experience with LangChain, LangGraph, LlamaIndex, or similar AI orchestration frameworks. Knowledge of vector databases and semantic search technologies. Experience with Python alongside TypeScript. Familiarity with Kubernetes, Docker, Infrastructure as Code ...

experience in AI/ML with experience developing and deploying solutions using LLMs, RAG architectures, and modern AI frameworks and protocols (Strands, FastMCP, LangChain, LlamaIndex, Hugging Face, A2A, MCP).Ability to translate multi-layered business problems into technical solutions with experience working directly with business stakeholders to understand requirements ...

experience in AI/ML with experience developing and deploying solutions using LLMs, RAG architectures, and modern AI frameworks and protocols (Strands, FastMCP, LangChain, LlamaIndex, Hugging Face, A2A, MCP).Ability to translate multi-layered business problems into technical solutions with experience working directly with business stakeholders to understand requirements ...

experience building applications on AWS or other public cloud platformsExperience with Generative AI systems, including: RAG (Retrieval-Augmented Generation) architectureAI orchestration frameworks (LangChain, LlamaIndex, etc.)LLM evaluation frameworks and responsible AI practices (guardrails, content filtering)Preferred Qualifications, Capabilities, and SkillsDeep expertise in Java, object-oriented design, and system designExperience with ...

approaches, including Graph-RAG and structured knowledge representation, where they deliver clear value. Required Skills & Experience Strong Python skills, with hands-on experience in LlamaIndex, LangChain, and LangGraph. Proven track record building RAG systems; Graph-RAG a distinct advantage. Hands-on fine-tuning, instruction tuning, and knowledge distillation, not just ...

Event streaming technologies such as Kafka, Pulsar, or Azure Event Hub Integration with Collibra Apache Iceberg Apache Arrow Pyspark AI engineering (Snowflake AI, Langchain, Llamaindex, Pinecone, etc) Insight is committed to being an inclusive employer and encourages applications from all suitably qualified applicants irrespective of background, circumstances, age, disability, gender ...

technical expertise in Generative AI development (e.g., prompt engineering, model tuning, vector databases like Vertex AI Vector Search, and AI frameworks like LangChain or LlamaIndex). Active participation in the startup and AI ecosystem, with a track record of public speaking, technical writing, or community contribution. Responsibilities: Deliver compelling presentations ...

robust production deployment. Desirable Skills Experience with Retrieval-Augmented Generation (RAG). Knowledge of vector databases. Experience with AI frameworks such as Haystack, LlamaIndex or Semantic Kernel. Experience with forecasting, anomaly detection or data classification. Knowledge of CNC, manufacturing, construction or other industrial environments would be advantageous ...

modern technologies including AI agents, LLMs and cloud-based systems Collaborative environment with opportunities to learn from experienced technical leaders Experience with LangChain, CrewAI, LlamaIndex, AWS, Vue.js or fintech platforms would be advantageous. ...