26 to 50 of 54 Pinecone Jobs in the UK

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 ...

with a strong emphasis on Python development in production environments Proven expertise in building and deploying generative AI applications, leveraging LLMs, vector databases like Pinecone, Weaviate, or pgvector, and modern open-source agentic frameworks Practical experience with microservices architecture, RESTful APIs, cloud platforms such as AWS, GCP, or Azure ...

locations, green values) with highly relevant sustainable vendor profiles and local circular economies. Infrastructure & Data Pipelines: Build and optimize scalable vector database infrastructures (e.g., Pinecone, Milvus, or pgvector) and real-time streaming architectures alongside backend tech stacks. Technical Leadership & Governance: Pioneer technical guardrails around AI model evaluation, data bias minimization ...

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 ...

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 ...

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: 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 ...

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 ...

models like Llama/Mistral) and orchestration frameworks (LangChain, LlamaIndex, Semantic Kernel, or equivalent). Practical expertise in RAG design, embeddings, and vector databases (Pinecone, Weaviate, pgvector, Azure AI Search). Experience with agentic architectures, function/tool calling, and structured outputs. Solid prompt engineering, evaluation, and LLM guardrail/ ...

building data, ML, or backend systems Python & ML/LLM Frameworks: Deep proficiency in Python with hands‐on experience using Hugging Face, LangChain, OpenAI, Pinecone, and related ecosystems Deployment & Infrastructure: Skilled in full-stack and API‐based deployment patterns, including Docker, FastAPI, Kubernetes, and cloud environments (GCP, AWS) Platform Orchestration ...

LLMs . Strong understanding of system design, microservices, event-driven architecture and cloud-native development . Experience working with PostgreSQL, MongoDB, Vector Databases (Qdrant, Pinecone, Weaviate or similar) . Comfortable working in ambiguous environments where priorities evolve quickly. Product-minded engineer who wants to own outcomes, not just tickets. Nice ...

Aurora, Athena or other similar large scale database technologies. Experience working with AI framework such as LangChain/LlamaIndex Experience with Vector databases (Pinecone, Weaviate, FAISS) This is an outline description of the key responsibilities and accountabilities involved in the job. This is not an exhaustive list and the post ...

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 ...

databases, and business logic to AI models in a standardized, secure way Experience with databases: SQL (PostgreSQL, MySQL), NoSQL (MongoDB, Redis), and vector databases (Pinecone, ChromaDB, Weaviate, or Qdrant). Strong understanding of software architecture, design patterns, and API design. Soft skills You lead with ownership and direction. ...

databases, and business logic to AI models in a standardized, secure way Experience with databases: SQL (PostgreSQL, MySQL), NoSQL (MongoDB, Redis), and vector databases (Pinecone, ChromaDB, Weaviate, or Qdrant). Strong understanding of software architecture, design patterns, and API design. Soft skills You lead with ownership and direction. ...

databases, and business logic to AI models in a standardized, secure way Experience with databases: SQL (PostgreSQL, MySQL), NoSQL (MongoDB, Redis), and vector databases (Pinecone, ChromaDB, Weaviate, or Qdrant). Strong understanding of software architecture, design patterns, and API design. Soft skills You lead with ownership and direction. ...

databases, and business logic to AI models in a standardized, secure way Experience with databases: SQL (PostgreSQL, MySQL), NoSQL (MongoDB, Redis), and vector databases (Pinecone, ChromaDB, Weaviate, or Qdrant). Strong understanding of software architecture, design patterns, and API design. Soft skills You lead with ownership and direction. ...

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 ...

software development practices (testing, code review, CI/CD). Hands-on experience with cloud-native ML infrastructure platforms. Knowledge of vector databases (e.g., Pinecone, Weaviate, Qdrant) and embedding models. Experience with model serving frameworks (e.g., vLLM, TensorRT, Ray). Background in forecasting, planning, or analytics applications. Experience with ...

working with AI tools and prompting. An understanding of point in time data is a strong plus Also desirable: experience with vector databases (pgvector, Pinecone, Weaviate, Qdrant or similar); machine learning experience (PyTorch, TensorFlow, XGBoost/LightGBM) for building, maintaining and extending existing models; Bloomberg API integration to Python; data ...

operating knowledge graphs or graph databases (e.g., Jena Fuseki, Neo4j, Amazon Neptune or equivalent). Experience with vector databases and embedding pipelines (e.g., Pinecone, Weaviate, Qdrant, pgvector). Practical experience implementing RAG architectures or LLM‐integrated data pipelines. Familiarity with semantic web standards — JSON‐LD, RDF, OWL, or SKOS. Strong ...

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/ ...

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