1 to 25 of 47 Pinecone Jobs in the UK

Platforms Experience with one or more: OpenAI Azure OpenAI Anthropic Claude Google Gemini AWS Bedrock Hugging Face LangChain LangGraph Semantic Kernel AutoGen CrewAI LlamaIndex Pinecone Weaviate Milvus ChromaDB Cloud Platforms Commercial experience with one or more: AWS Microsoft Azure Google Cloud Platform (GCP) Enterprise Data Data Engineering Data Platforms ...

vector search • Proven experience building agentic AI with LangGraph or similar (LangChain, Semantic Kernel, AutoGen, CrewAI) • Experience with vector databases (pgvector, Azure AI Search, Pinecone, Weaviate, Chroma, FAISS, Milvus or OpenSearch) • Cloud (Azure/AWS/GCP), Docker and Kubernetes • Solid grasp of API integration, tool/function calling ...

LangGraph, LlamaIndex, and Hugging Face, including agentic and multi‐step workflowsProven experience designing and implementing Retrieval‐Augmented Generation (RAG) systems, including vector databases (pgvector, Pinecone, Weaviate, FAISS, etc.) and advanced retrieval strategies (hybrid search, re‐ranking, metadata filtering)Strong understanding of prompt engineering, workflow design, and Gen‐AI optimization, balancing ...

least one hyperscaler ML platform (SageMaker, Azure ML, or Vertex AI).Generative AI: LLM fine-tuning (LoRA/QLoRA), RAG architecture design, vector databases (Pinecone, Milvus, Weaviate), and agentic frameworks (LangChain, LangGraph, Semantic Kernel).Data pipelines: data lake/lakehouse architectures, ETL/ELT, and data quality/lineage tooling ...

experience with AI system design, architecture, and distributed systems Expertise in API-based backend development (e.g. FastAPI or similar) Experience with vector databases (e.g. Pinecone, Chroma) Experience with agent frameworks (e.g. LangChain, LangGraph, or similar) Strong understanding of evaluation frameworks for AI/agent systems Experience implementing CI/ ...

ability to explain technical concepts to both technical and non-technical stakeholders. Desirable Experience AI agents and agentic workflows. Vector databases such as Pinecone, Weaviate, or pgvector. Feature stores including Feast or AWS Feature Store. Docker, Kubernetes, or Amazon ECS. Infrastructure as Code using Terraform or CloudFormation. Big data processing ...

operate, support, and secure mission-critical applications Previous experience deploying and managing LLM-model based applications and agentsExposure to vector stores such as Pinecone, GCP RAG engine, and AWS S3 Vector BucketsExposure to cloud-native microservices architectureFamiliarity with advanced AI/ML concepts and protocols, including Retrieval-Augmented Generation ...

embeddings, prompt engineering or fine tuning Exposure to LangChain, LangGraph, Agent Development Kit or similar agent frameworks Experience with vector databases such as Pinecone, Chroma or similar API development experience, ideally with FastAPI or similar frameworks Knowledge of MLOps, LLMOps, CI/CD or production deployment practices Experience designing ...

embeddings, prompt engineering or fine tuning Exposure to LangChain, LangGraph, Agent Development Kit or similar agent frameworks Experience with vector databases such as Pinecone, Chroma or similar API development experience, ideally with FastAPI or similar frameworks Knowledge of MLOps, LLMOps, CI/CD or production deployment practices Experience designing ...

embeddings, prompt engineering or fine tuning Exposure to LangChain, LangGraph, Agent Development Kit or similar agent frameworks Experience with vector databases such as Pinecone, Chroma or similar API development experience, ideally with FastAPI or similar frameworks Knowledge of MLOps, LLMOps, CI/CD or production deployment practices Experience designing ...

memory, and workflow orchestration using LangChain, CrewAI, AutoGen, ADK and LangGraph.Implement Retrieval-Augmented Generation (RAG) pipelines and semantic search using vector databases such as Pinecone and Chroma, including indexing, retrieval policies, and evaluation.Build and integrate agent tools (MCP) and APIs to connect agents with external services, databases, and internal systems ...

tools/functions callable by AI agents (tool schemas, function calling, structured outputs). Experience with retrieval-augmented generation (RAG): vector databases (eg, 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 ...

knowledge graphs for context enrichment, reasoning, and workflow automationRAG & Knowledge Systems: End-to-end RAG pipelines using enterprise search + vector stores (e.g., Elastic, Pinecone) with grounding, evaluation, and optimizationModel Lifecycle & Governance: Model evaluation, monitoring, prompt/version control, and Responsible AI/MRM complianceEnterprise AI Integration & DataAPI- and event ...

with 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 ...

communication skills with the ability to explain technical concepts to both technical and non-technical stakeholders.Desirable ExperienceAI agents and agentic workflows.Vector databases such as Pinecone, Weaviate, or pgvector.Feature stores including Feast or AWS Feature Store.Docker, Kubernetes, or Amazon ECS.Infrastructure as Code using Terraform or CloudFormation.Big data processing technologies such ...

platforms including GitHub, GitLab, Jenkins, or similar.Familiarity with monitoring and observability tools for AI applications and services.Database TechnologiesExperience with vector databases such as ChromaDB, Pinecone, PGVector, Qdrant, MongoDB, or similar solutions.Familiarity with NoSQL databases.Experience working with SQL databases, particularly PostgreSQL or equivalent.Version ControlStrong experience using Git and modern version control ...

GitLab, Jenkins, or similar. Familiarity with monitoring and observability tools for AI applications and services. Database Technologies Experience with vector databases such as ChromaDB, Pinecone, PGVector, Qdrant, MongoDB, or similar solutions. Familiarity with NoSQL databases. Experience working with SQL databases, particularly PostgreSQL or equivalent. Version Control Strong experience using ...

platforms including GitHub, GitLab, Jenkins, or similar.Familiarity with monitoring and observability tools for AI applications and services.Database TechnologiesExperience with vector databases such as ChromaDB, Pinecone, PGVector, Qdrant, MongoDB, or similar solutions.Familiarity with NoSQL databases.Experience working with SQL databases, particularly PostgreSQL or equivalent.Version ControlStrong experience using Git and modern version control ...

platforms including GitHub, GitLab, Jenkins, or similar.Familiarity with monitoring and observability tools for AI applications and services.Database TechnologiesExperience with vector databases such as ChromaDB, Pinecone, PGVector, Qdrant, MongoDB, or similar solutions.Familiarity with NoSQL databases.Experience working with SQL databases, particularly PostgreSQL or equivalent.Version ControlStrong experience using Git and modern version control ...

pipelines and integrating with enterprise systems (REST, Python, SQL, GraphQL, Webhooks etc). Solid understanding of LLMs, Prompt engineering/tuning, Vector DBs (AstraDB, Pinecone, Weaviate etc), RAG pipelines (LlamaIndex, Haystack) and Agent/Workflow Orchestration (LangChain, LangGraph, CrewAI) Knowledge of SLM Finetuning and Distillation is big advantage. Experience ...

powered applications in enterprise SaaS or complex data platforms. AI & Engineering Mastery: Deep technical expertise in Python or Go, semantic search, vector databases (e.g., Pinecone, Milvus, pgvector), orchestration frameworks (LangChain, LlamaIndex), and fine-tuning or prompt engineering of state-of-the-art Large Language Models (LLMs). Extreme Ownership: High ...

Gemini, open-weight models) with tools, data, and external systems through MCP and custom connectors. Apply RAG techniques where they actually help: vector databases (Pinecone, Chroma, Weaviate, pgvector),hybrid retrieval with ElasticSearch or Solr, and BM25 + similarity search. Work across relational, document, key-value, and graph stores ...

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 ...

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 ...

methodologies and version control systems like Git. Exposure to cloud platforms (AWS, Azure, or Google Cloud). Basic awareness of Vector Databases (e.g., pgvector, Pinecone) or RAG (Retrieval-Augmented Generation) concepts. Any foundational Blue Prism certifications. Why You Will Love It Here! Flexibility: Hybrid Work ModelYour Future: Professional Development Reimbursement ...