26 to 37 of 37 Weaviate Jobs in the UK

Engineer or Senior DeveloperHas breadth of experience across different tech-stacks, such as JavaScript/TypeScript, Java, C#, or Python, amongst othersExperienced in RAG Weaviate, OpenAI, Agents, MCP, Langchain, Prompt Engineering, Browser-Use, and DjangoExperienced building AI Tools, Agents and Agentic workflows (LangGraph, CrwAI)Hands-on Product building experience that ...

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 ...

weight models) with tools, data, and external systems through MCP and custom connectors. Apply RAG techniques where they actually help: vector databases (Pinecone, Chroma, Weaviate, pgvector),hybrid retrieval with ElasticSearch or Solr, and BM25 + similarity search. Work across relational, document, key-value, and graph stores as the problem demands ...

Deep GenAI & RAG Expertise: 2+ years of hands‐on experience building and productionising LLM applications, with deep technical knowledge of vector databases (e.g., Qdrant, Weaviate, Pinecone, pgvector) and orchestration layers (e.g., LangGraph, LlamaIndex). Comfortable working with heterogeneous documents like pdfs. Experience working with re‐ranking models. Production-Grade Asynchronous ...

/executor/verifier patterns, tool‐use schemas, retry + escalation logic. Build retrieval pipelines: chunking strategy, vector DB choice (Pinecone/pgvector/Weaviate), reranking, freshness handling. Stay current on Anthropic + OpenAI release notes; adjust prompts + schemas when APIs evolve. We treat the foundation‐model contract ...

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/ ...

building and operating knowledge graphs or graph databases (e.g. Jena Fuseki, Neo4j, AmazonNeptune, or equivalent)Experience with vector databases and embedding pipelines (e.g. Pinecone, Weaviate, Qdrant, pgvector)Practical experience implementing RAG architectures or LLM-integrated data pipelinesFamiliarity with semantic web standards — JSON-LD, RDF, OWL, or SKOSStrong Python skills ...

secrets management Pragmatic mindset with a strong sense of ownership Excellent communication and collaboration skills Nice-to-have MongoDB and OpenSearch Vector databases (Qdrant, Weaviate, Milvus, Pinecone, pgvector) OIDC or identity infrastructure Infisical, PostHog, Oh Dear, or similar tooling AI/LLM platform experience GDPR-conscious cloud environments Enterprise security ...

architectures that drive real value for the business. Core Stack Python: Expert level AI Frameworks: LangChain, CrewAI, AutoGPT-style frameworks Vector Databases: Pinecone, Milvus, Weaviate Architecture: LLM orchestration and tool-calling pipelines API Design: REST and GraphQL What Sets This Role Apart Deep Reasoning: Deep understanding of LLM reasoning loops. ...

model deployment pipelines, monitoring, versioning, and automated testing frameworks for AI applications Some other highly valued skills may include: Experience with vector stores (Pinecone, Weaviate, or AWS OpenSearch) and semantic search implementations for context-aware AI applications Experience building RESTful or GraphQL APIs and designing scalable, event-driven architectures ...

traffic management for PostgreSQL, especially PgBouncer, HAProxy, Kubernetes service routing, or comparable patterns.Practical VectorDB or vector search experience, such as pgvector, Qdrant, Milvus, Weaviate, OpenSearch vector search, or similar systems.Ability to reason about vector index types and operational tradeoffs, including HNSW/IVFFlat-style indexes, recall, latency, memory, ingestion throughput ...

across client use cases Work across LangGraph, LangChain, Claude Code/Codex/Gemini and RAG pipelines Implement RAG and vector database solutions (Pinecone, Weaviate, LlamaIndex) Deploy across cloud platforms: AWS Bedrock, GCP Vertex AI or Azure AI Studio Bridge CX and engineering Hold the full stack from CX design … 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 Leadership & consulting skills Clear communication; able to explain technical decisions ...