8 of 8 Remote/Hybrid Pinecone Jobs in London

Experience building RESTful APIs and microservices. Knowledge of software design patterns and scalable application architecture. AI Application Development Retrieval-Augmented Generation (RAG) Vector databases: Pinecone ChromaDB Weaviate Azure AI Search Embedding models and semantic search. Model evaluation and observability. Desirable skills/knowledge/experience: Azure, AWS, or Google Cloud ...

continuous integration and deployment tools such as **GitLab**, **GitHub**, or **Jenkins**.## **Database Management*** Vector Databases: Experience with and (but not limited to) ChromaDB, Pinecone, PGVector, MongoDB , Qdrant etc.* NoSQL: Familiarity with NoSQL databases (e.g., MongoDB preferred).* SQL: Experience working with SQL databases like PostgreSQL.## **Version Control*** Proficient ...

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 ...

learning concepts, embeddings, transformers, and LLM architectures.* Experience using LangChain, LangGraph, LlamaIndex, AutoGen, MCP, or similar AI frameworks.* Experience with vector databases such as Pinecone, Weaviate, Milvus, Qdrant, ChromaDB, or equivalent.* Experience with graph databases, knowledge graphs, or Graph APIs.* Experience building data pipelines and integrating structured and unstructured data ...

technical 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 ...

critically and effectively as part of their day-to-day workflow. Bonus points for: Experience with retrieval-augmented generation (RAG) and vector databases (pgvector, Pinecone, or similar). Experience designing multi-agent systems and agent orchestration patterns. Familiarity with LLM observability tools (LangSmith, Langfuse, Arize, or similar). Experience working ...

cases and ML, AI opportunities. Experience with containerisation technologies ( Docker, Kubernetes ) for scalable data solutions. Experience with vector databases and graph databases (e.g., Pinecone, Neo4j, AWS Neptune ). Understanding of data mesh-fabric approaches and modern data architecture patterns . Familiarity with AI/ML workflows and their data requirements. ...

high-performance APIs and caching strategies enabling low‐latency data access for AI agents and orchestration systems. Implement vector-based data retrieval layers (pgVector, Pinecone) and ensure efficient embedding pipelines for AI contexts. Partner with AI teams to monitor data latency, cost efficiency, and observability metrics. Collaboration & Governance Partner with ...