1 to 25 of 31 Weaviate Jobs in England

/unsupervised ML and AI observability Experience in Enterprise-grade RAG-based solutions with LLMs (OpenAI, Hugging Face, LLaMA, etc.) and vector databases (Pinecone, Weaviate, FAISS). Experience in designing and scaling GenAI chatbots. Experience in Agentic AI solutions. Good knowledge of Agentic AI frameworks (LangGraph, AutoGen, CrewAI) and orchestration ...

governance, compliance, and model risk management. Experience with LangChain, LangGraph, LlamaIndex, CrewAI, Semantic Kernel, or similar frameworks. Familiarity with vector databases such as Pinecone, Weaviate, ChromaDB, or pgVector. Experience implementing observability and monitoring solutions for AI platforms. Understanding of event-driven architectures, messaging platforms, and enterprise integration patterns. Exposure ...

with experience developing scalable APIs, AI services, and automation solutions.* Experience implementing vector search solutions using Vector Databases such as Azure AI Search, Pinecone, Weaviate, Chroma, Milvus, or similar technologies.* Experience working with Large Language Models (LLMs) such as GPT, Llama, Claude, Mistral, or equivalent foundation models.* Strong understanding ...

Azure OpenAI, AWS Bedrock, OpenAI API, or open‐source models such as Llama and Mistral. Experience with vector databases and embedding workflows, including Chroma, Weaviate, pgvector, Azure AI Search, or equivalent. Solid understanding of CI/CD pipelines for application code and ML/AI artifacts, including MLflow ...

platform (SageMaker, Azure ML, or Vertex AI). Generative AI: LLM fine-tuning (LoRA/QLoRA), RAG architecture design, vector databases (Pinecone, Milvus, Weaviate), and agentic frameworks (LangChain, LangGraph, Semantic Kernel). Data pipelines: data lake/lakehouse architectures, ETL/ELT, and data quality/lineage tooling that feed ...

vision, and delivering complex, cross‐team projects. English — advanced proficiency, written and spoken. Preferred Qualifications Fine‐tuning, RLHF, or model customization. Vector databases (Pinecone, Weaviate, or FAISS) and embedding retrieval. Building agent workflows with MCP servers or modern agent frameworks. Conversational AI and speech (speech‐to‐text/text ...

Azure)* CI/CD pipelines* Scalable service architectureData and Retrieval Systems* Experience building and operating knowledge layers* Vector databases (e.g. Pinecone, Weaviate, pgvector)* Document ingestion pipelines* Embedding workflows* Search and retrieval optimization**Nice to Have Experience with:*** MCP architectures or tool-connected AI systems* Agent frameworks* Knowledge graph systems* Streaming ...

integrating with enterprise systems (REST, Python, SQL, GraphQL, Webhooks etc). Solid understanding of LLMs, Prompt engineering/tuning, Vector DBs (AstraDB, Pinecone, Weaviate etc), RAG pipelines (LlamaIndex, Haystack) and Agent/Workflow Orchestration (LangChain, LangGraph, CrewAI). Knowledge of SLM Finetuning and Distillation is big advantage. Experience and knowledge ...

ideally in a regulated environment. Preferred qualifications: Background in financial services or 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 ...

LangChain, Semantic Kernel, or AutoGen. Hands-on experience with Model Context Protocol (MCP) implementations. Strong understanding of vector databases and technologies such as Pinecone, Weaviate, FAISS, or Azure AI Search. Experience building and supporting Retrieval-Augmented Generation (RAG) solutions. Experience working with OpenAI and other modern AI platforms. Expertise ...

integrating with enterprise systems (REST, Python, SQL, GraphQL, Webhooks etc). Solid understanding of LLMs, Prompt engineering/tuning, Vector DBs (AstraDB, Pinecone, Weaviate etc), RAG pipelines (LlamaIndex, Haystack) and Agent/Workflow Orchestration (LangChain, LangGraph, CrewAI) Knowledge of SLM Finetuning and Distillation is big advantage. Experience and knowledge ...

Foundry or Microsoft Agent Framework Knowledge of MCP and A2A protocols for agent and tool interoperability Hands-on work with vector databases like Pinecone, Weaviate, Qdrant or pgvector Familiarity with distributed systems, workflow engines (Temporal, Airflow or Dagster) and event-driven architectures Experience with open-source LLMs or Small Language ...

Artificial Intelligence, Machine Learning, or a strongly related quantitative field Hands‐on experience with cloud‐native ML infrastructure platforms Knowledge of vector databases (Pinecone, Weaviate, Qdrant) and embedding models Experience with model serving frameworks (vLLM, TensorRT, Ray) Experience with A/B testing and experimentation frameworks for AI features Contributions ...

open‐weight models) with tools, data, and external systems through MCP and custom connectors. Apply RAG techniques where they actuallyhelp:vector databases (Pinecone, Chroma,Weaviate,pgvector), hybrid retrieval withElasticSearchorSolr, and BM25 + similarity search. Work across relational, document, key‐value, and graph stores as the problem demands; use event‐driven ...

Agentic 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 ...

Agentic 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 ...

models like Llama/Mistral) and orchestration frameworks (LangChain, LlamaIndex, Semantic Kernel, or equivalent). Practical experience with RAG, embeddings, and vector databases (Pinecone, Weaviate, pgvector, Azure AI Search). Familiarity with agentic architectures, function/tool calling, and structured outputs. Prompt engineering and evaluation experience, with awareness of guardrails ...

like Llama/Mistral) and orchestration frameworks (LangChain, LlamaIndex, Semantic Kernel, or equivalent). Practical expertise in RAG design, embeddings, and vector databases (Pinecone, Weaviate, pgvector, Azure AI Search). Experience with agentic architectures, function/tool calling, and structured outputs. Solid prompt engineering, evaluation, and LLM guardrail/safety ...

like Llama/Mistral) and orchestration frameworks (LangChain, LlamaIndex, Semantic Kernel, or equivalent). Proven expertise in RAG design, embeddings, and vector databases (Pinecone, Weaviate, pgvector, Azure AI Search). Experience with agentic architectures, function/tool calling, and structured outputs. Strong prompt engineering, evaluation, and LLM guardrail/safety ...

tools/functions callable by AI agents (tool schemas, function calling, structured outputs). Experience with retrieval-augmented generation (RAG) : vector databases (e.g., Pinecone, Weaviate, pgvector), embeddings, and chunking strategies. Working knowledge of prompt engineering and evaluation techniques for agent reliability, safety, and cost control. Familiarity with orchestrating multi-agent ...

strong emphasis on Python development in production environments Proven expertise in building and deploying generative AI applications, leveraging LLMs, vector databases like Pinecone, Weaviate, or pgvector, and modern open-source agentic frameworks Practical experience with microservices architecture, RESTful APIs, cloud platforms such as AWS, GCP, or Azure, and containerization with ...

software development practices (testing, code review, CI/CD).DesirableHands-on experience with cloud-native ML infrastructure platforms. Knowledge of vector databases (e.g., Pinecone, Weaviate, Qdrant) and embedding models. Experience with model serving frameworks (e.g., vLLM, TensorRT, Ray).Background in forecasting, planning, or analytics applications. Experience with A/ ...

with major agent or LLM orchestration frameworks such as LangChain, LlamaIndex, LangGraph, OpenAI Agents SDK, or CrewAI. Experience with vector databases such as Pinecone, Weaviate, pgvector, Qdrant, or similar systems. Experience with enterprise AI use cases in financial services, legal, consulting, enterprise SaaS, sales, marketing, or internal knowledge management. Track ...

right job. Our AI engineering stack includes: AI/ML Core: LangChain, LlamaIndex for orchestration Hugging Face transformers and inference Vector databases (Pinecone, Weaviate, Qdrant) Custom evaluation and monitoring tools Python (FastAPI) for AI services TypeScript, React, Next.js for AI-powered interfaces PostgreSQL with pgvector Real-time streaming ...

practices (testing, code review, CI/CD). Preferred Skills Hands‐on experience with cloud‐native ML infrastructure platforms Knowledge of vector databases (Pinecone, Weaviate, Qdrant) and embedding models Experience with model serving frameworks (vLLM, TensorRT, Ray) Familiarity with Anaplan or similar enterprise planning platforms Experience with A/ ...