14 of 14 Weaviate Jobs in London

/LLMOps pipelines, and AI observability. Experience in Enterprise-grade RAG-based solutions with LLMs (OpenAI, Hugging Face, LLaMA, etc.) and vector databases (Pinecone, Weaviate, FAISS, etc.). Ability to design enterprise-level AI/Gen AI platform/solutions with the client's existing enterprise stack. Hands-on mastery ...

Hands-on experience with GenAI frameworks such as LangChain, LlamaIndex, AutoGen, CrewAI or LangGraph . Experience designing AI systems using vector databases (e.g. Pinecone, Weaviate, FAISS). Solid understanding of prompt engineering, model tuning, and AI evaluation methodologies . Experience building production-grade AI systems using Python and ML frameworks ...

with GenAI frameworks such as LangChain, LlamaIndex and agent frameworks like AutoGen, CrewAI or LangGraph . Experience building RAG architectures with vector databases (Pinecone, Weaviate, FAISS). Strong understanding of MLOps/LLMOps (MLflow, Kubeflow, Docker, Kubernetes). Experience deploying AI solutions on AWS, Azure or GCP . Solid software ...

production-ready AI systems. Experience in designing and implementing enterprise-grade AI solutions, including RAG-based solutions with LLMs and vector databases (e.g., Pinecone, Weaviate, FAISS). Proven experience in full stack development and AI/ML system implementation within enterprise environments. Strong grasp of advanced techniques such as complex ...

. Knowledge of MLOps workflows and ML tooling. Clear communication and a collaborative mindset. Nice‐to‐Haves Experience with LangChain, vector databases (Pinecone, Weaviate etc), or agent frameworks. Track record of advanced side projects or research contributions. Full stack familiarity (e.g., React, Postgres, TypeScript) is a plus. 💼 Why Join ...

Well Help You With Them Experience with advanced LLM techniques: agents, tool use, and agentic workflows Experience with vector databases (Pinecone, Weaviate, pgvector) for RAG applications Experience with feature stores (Feast, AWS Feature Store) Experience with containerisation (Docker) and orchestration (Kubernetes, ECS) Familiarity with Infrastructure as Code (Terraform, CloudFormation) Experience ...

fast without compromising on code quality, testing, and operational excellence . Nice to have Experience with tools such as LangChain, LlamaIndex, Haystack, Hugging Face, Weaviate, CrewAI, AutoGen , or similar. Hands-on work with Retrieval Augmented Generation , AI agents, and agent orchestration frameworks. Experience working with unstructured data (documents, conversations, images ...

experience of: Agent Orchestration: LangChain, LangGraph, CrewAI - not just conceptual Agentic Coding Tools: Claude Code CLI, Cursor, OpenAI Codex, Copilot RAG & Vector Stores: Chroma, Weaviate, Pinecone, know where RAG breaks LLM APIs & SDKs: Anthropic, OpenAI, Gemini - prompt design, tool use Python/TypeScript: Primary languages for agent + backend development ...

capabilities across the platform — from content generation to account intelligence and campaign automation. Design and implement RAG pipelines using vector databases like Qdrant or Weaviate for contextual awareness and retrieval. Build robust backend services in TypeScript to serve AI-driven features, including streaming, tool use, and human-in-the-loop ...

CrewAI) in production. Strong Python engineering skills with solid testing, optimisation, CI/CD, and code quality; Experience implementing and scaling vector databases (Pinecone, Weaviate, Milvus) for retrieval and reasoning workloads. Deep expertise in cloud‐native AI engineering on AWS, with Azure knowledge and ability to design distributed, fault‐tolerant ...

deployed roles Strong Python Experience building and deploying LLM applications (OpenAI, Anthropic, Gemini, etc.) Deep familiarity with RAG methodologies, embeddings, and vector databases (Pinecone, Weaviate, pgvector) Robust API integration experience, including working with third-party datasets, web APIs, or scrapers A product mindset, enjoys crafting scrappy prototypes that evolve into ...

deployed roles Strong Python Experience building and deploying LLM applications (OpenAI, Anthropic, Gemini, etc.) Deep familiarity with RAG methodologies, embeddings, and vector databases (Pinecone, Weaviate, pgvector) Robust API integration experience, including working with third-party datasets, web APIs, or scrapers A product mindset, enjoys crafting scrappy prototypes that evolve into ...

years focused on information retrieval, search systems, NLP, or RAG architectures. ● Deep expertise in vector databases — production experience with at least one of: Pinecone, Weaviate, Milvus, Qdrant, Chroma, pgvector, or Databricks Vector Search. Understanding of index types, distance metrics, sharding, and performance tuning. ● Hands-on experience with embedding models — OpenAI … product architectures in the context of serving retrieval use cases. Technical Stack ● Retrieval Orchestration LangGraph - LangChain, Pydantic.AI ● Vector Databases - Databricks Vector Search, Pinecone/Weaviate/Milvus/pgvector ● Knowledge Graphs - Neo4j, Amazon Neptune, or TigerGraph ● Data Platform - Databricks (Delta Lake, Unity Catalog, Spark SQL, MLflow) ● Embedding models - OpenAI, Cohere ...

cost. Design and run cloud-native AI services across AWS and Databricks, including ingestion and embedding pipelines. Scale and operate vector search infrastructure (Weaviate, OpenSearch, Algolia, AWS Bedrock Knowledge Bases). Implement strong observability, CI/CD, security, and governance across AI workloads. Enable future architectures such as multi-model … large-scale data or embedding pipelines. Proven experience building and operating production AI systems , including RAG pipelines, LLM-backed services, and vector search (Weaviate, OpenSearch, Algolia). Proficiency in Python , with experience deploying containerised services on Kubernetes using Terraform . Solid understanding of distributed systems, cloud architecture, and API design ...