26 to 50 of 104 LlamaIndex Jobs in the UK

MLOps, observability, and cloud-native AI deploymentExcellent communication, problem-solving, and project management skills in agile environmentsBonus Points ForExperience with agentic frameworks (e.g., LangChain, LlamaIndex)Experience in deep learning frameworks and front-end developmentFamiliarity with Langfuse, Langsmith, or other LLM observability toolsUnderstanding of Model Context Protocol and bias/hallucination ...

essential, not just RAG in isolation: Semantic search, vector/embedding infrastructure, and retrieval architecture design LLM orchestration and agentic frameworks (eg LangChain/LlamaIndex-style tooling, multi-agent patterns) LLM evaluation, guardrails, and red-teaming tooling (hallucination detection, safety/bias testing) LLMOps/MLOps: model versioning, deployment pipelines ...

being designed and built.Bonus PointsExperience with any of the following would be highly advantageous:AI gateways and model routingPrompt management platformsAI evaluation frameworksLangGraph, LangChain, LlamaIndex, DSPy, CrewAI or similar orchestration frameworksVector databases and semantic retrievalKnowledge graphs or document understanding systemsBuilding internal AI platforms used by multiple engineering teamsBenefitsWe ...

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 ...

agentic AI systems — including LLM-powered application design, retrieval-augmented generation (RAG) architectures, and at least one agentic AI framework (e.g. LangGraph, LangChain, LlamaIndex, CrewAI) Experience designing and building data and context pipelines for AI systems — including embedding pipelines, vector databases, and semantic search applied to structured commerce data Familiarity ...

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 ...

another regulated enterprise environment. Experience with vector databases (for example pgvector, Pinecone, Weaviate, or Chroma) and agent or orchestration frameworks (for example LangChain, LlamaIndex, or the Model Context Protocol). Experience with MLOps/LLMOps tooling such as experiment tracking, model versioning, monitoring, evaluation/observability platforms, or CI/ ...

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 ...

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 ...

cross-functional teams and mentor others 7+ years software engineering experience 2+ years hands-on in AI/ML & GenAI solutions Experience with LangChain, LlamaIndex, CrewAI, or similar Knowledge of RAG, vector databases, and semantic search Experience with APIs, microservices, and cloud-native architecture Nice to Have AWS certifications ...

proposals Candidates should have strong experience in AI Engineering, MLOps and cloud-native AI platforms, alongside hands-on knowledge of technologies such as LangChain, LlamaIndex, MLflow, Kubernetes, Docker and CI/CD tooling. Applicants will ideally demonstrate: * Experience working in a major Consulting firm, and/or in industry ...

MySQL, Oracle, SQL, Postgres, RDS, Aurora, Athena or other similar large scale database technologies. Experience working with AI framework such as LangChain/LlamaIndex Experience with Vector databases (Pinecone, Weaviate, FAISS) This is an outline description of the key responsibilities and accountabilities involved in the job. This ...

complex data platforms. AI & Engineering Mastery: Deep technical expertise in Python or Go, semantic search, vector databases (e.g., Pinecone, Milvus, pgvector), orchestration frameworks (LangChain, LlamaIndex), and fine-tuning or prompt engineering of state-of-the-art Large Language Models (LLMs). Extreme Ownership: High-agency mindset. You don’t wait ...

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 ...

frameworks: LangGraph, LangChain, CrewAI, Agentforce or similar Foundation model providers: Claude Code/Codex/Gemini, OpenAI or AWS Bedrock Vector databases: Pinecone, Weaviate, LlamaIndex or pgvector Cloud platforms: AWS Bedrock, GCP Vertex AI or Azure AI Studio CI/CD for AI: version-controlled prompts, automated testing, deployment pipelines ...

frameworks: LangGraph, LangChain, CrewAI, Agentforce or similar Foundation model providers: Claude Code/Codex/Gemini, OpenAI or AWS Bedrock Vector databases: Pinecone, Weaviate, LlamaIndex or pgvector Cloud platforms: AWS Bedrock, GCP Vertex AI or Azure AI Studio CI/CD for AI: version‐controlled prompts, automated testing, deployment pipelines ...

frameworks: LangGraph, LangChain, CrewAI, Agentforce or similar Foundation model providers: Claude Code/Codex/Gemini, OpenAI or AWS Bedrock Vector databases: Pinecone, Weaviate, LlamaIndex or pgvector Cloud platforms: AWS Bedrock, GCP Vertex AI or Azure AI Studio CI/CD for AI: version-controlled prompts, automated testing, deployment pipelines ...

Pandas, scikit-learn) and applying object-oriented programming principles to develop efficient, scalable solutionsHands-on experience experimenting with Generative AI (e.g. LangChain, Hugging Face, LlamaIndex).Experience working with Azure data & AI services such as Azure Machine Learning, Foundry etc.Practical experience working in Agile environments and contributing to sprints, stand ...

frameworks, benchmarking systems, or automated testing pipelinesHands-on experience with agentic workflows, tool-using AI systems, or multi-agent coordination (examples include: langgraph, AutoGPT, LLamaIndex)Experience with data-centric ML approaches including synthetic data generation, data curation, or curriculum learning pipelinesExperience training large-scale models over distributed nodes with cloud ...