4 of 4 Permanent Weaviate Jobs in the City of London

. 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 ...

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 ...

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 ...

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 ...