26 to 49 of 49 Pinecone Jobs in the UK

multi-agent workflows and autonomous AI systems Knowledge of the Model Context Protocol (MCP) and AI integration patterns Experience with vector databases such as Pinecone, Weaviate, FAISS, or Azure AI Search Experience working with OpenAI and other leading foundation models Knowledge of real-time AI pipelines, including speech-to-text ...

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 ...

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 ...

securely, and consistently across teams. Retrieval-Augmented Generation (RAG) & Knowledge Architecture: Expertise architecting RAG and knowledge-grounded systems—chunking strategies, embeddings, vector databases (e.g., Pinecone, Weaviate, Chroma, pgvector, FAISS), hybrid search, reranking, and retrieval evaluation. Familiarity with advanced patterns such as GraphRAG and agentic RAG to maximize factual grounding … Semantic Kernel, CrewAI, AutoGen). Experience with cloud AI platforms (e.g., Amazon Bedrock, Azure OpenAI/AI Foundry, Google Vertex AI), vector databases (e.g., Pinecone, Weaviate, Chroma, pgvector, FAISS), containerization and orchestration (Docker, Kubernetes), and distributed computing is advantageous. Architecture Design: Ability to design end-to-end Generative and Agentic ...

with: 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 ...

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 with multiple ...

with: 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 ...

with: 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 ...

with: 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 ...

Science, 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 ...

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. ...

Science, 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 ...

Computer Science, Artificial Intelligence, Machine Learning, or a strongly related quantitative fieldHands-on experience with cloud-native ML infrastructure platformsKnowledge of vector databases (Pinecone, Weaviate, Qdrant) and embedding modelsExperience with model serving frameworks (vLLM, TensorRT, Ray)Experience with A/B testing and experimentation frameworks for AI featuresContributions to open ...

Architect agent loops: planner/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 ...

experience taking systems from idea to production and keeping them running. Modern GenAI tooling – You have hands-on experience with libraries and tools like Pinecone, HuggingFace, LangChain/LangSmith, or CrewAI, and you know how to pick the right tool for the job. Understanding of agentic architectures – You're comfortable ...

just prototypes Demonstrable experience of building and deploying complex AI applications using LLMs and ideally, agentic workflows A familiarity with vector databases (pgvector, ChromaDB, Pinecone or similar) is a plus Benefits include: Flexibility - the team works fully remotely, albeit with frequent meetups to share ideas Stock options Excellent opportunities ...

essential) Practical experience with AI development concepts such as prompt engineering, AI agent development, RAG, and vector databases/semantic search (e.g., Pinecone, Azure AI Search, Chroma) Familiarity with Microsoft Azure services Please note that there is an in-office requirement of 3 days a week in their City ...

development 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/ ...

infrastructureExperience 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 ...

just prototypes Demonstrable experience of building and deploying complex AI applications using LLMs and ideally, agentic workflows A familiarity with vector databases (pgvector, ChromaDB, Pinecone or similar) is a plus Benefits include: Flexibility - the team works fully remotely, albeit with frequent meetups to share ideas Stock options Excellent opportunities ...

streaming technologies such as Kafka, Pulsar, or Azure Event Hub Integration with Collibra Apache Iceberg Apache Arrow Pyspark AI engineering (Snowflake AI, Langchain, Llamaindex, Pinecone, etc) Insight is committed to being an inclusive employer and encourages applications from all suitably qualified applicants irrespective of background, circumstances, age, disability, gender identity ...

models for complex reaction networks, define the semantic ontologies that let AI reason across different chemical data types, and design vector search (e.g. pgvector, Pinecone) for similarity lookups across large molecular sets. Design the telemetry pipeline. Specify streaming ingestion for high-frequency robot and sensor data, with zero loss ...

Author custom skills and slash commands for Claude Code to codify team‐specific workflows. Implement RAG pipelines and integrate vector stores (e.g., Qdrant, pgvector, Pinecone) to ground agent outputs in trusted data. Instrument agents for evaluation and observability so their outputs can be verified, measured, and audited. Apply AI‐specific … Model Context Protocol) for connecting agents to internal tools and data sources. Working knowledge of RAG patterns and vector store integration (e.g., Qdrant, pgvector, Pinecone). Awareness of AI‐specific risk areas relevant to a regulated environment (OWASP LLM Top 10, hallucination/determinism concerns, and auditability of agent decisions ...

Author custom skills and slash commands for Claude Code to codify team-specific workflows. Implement RAG pipelines and integrate vector stores (e.g. Qdrant, pgvector, Pinecone) to ground agent outputs in trusted data. Instrument agents for evaluation and observability so their outputs can be verified, measured, and audited. Apply AI-specific … Model Context Protocol) for connecting agents to internal tools and data sources. Working knowledge of RAG patterns and vector store integration (e.g. Qdrant, pgvector, Pinecone).Awareness of AI-specific risk areas relevant to a regulated environment (OWASP LLM Top 10, hallucination/determinism concerns, and auditability of agent decisions).Why ...