1 to 25 of 61 Pinecone Jobs in the UK

ensuring reliable, secure, and consistent operation. Retrieval‐Augmented Generation (RAG) & Knowledge Architecture – expertise in RAG and knowledge‐grounded systems, including chunking, embeddings, vector databases (Pinecone, Weaviate, Chroma, pgvector, FAISS), hybrid search and retrieval evaluation. Familiarity with GraphRAG and agentic RAG. LLMOps, Evaluation & Responsible AI – operationalizing LLM and agentic systems ...

Supervised/unsupervised ML and AI observability•Experience in Enterprise-grade RAG-based solutions with LLMs (OpenAI, Hugging Face, LLaMA, etc.) and vector databases (Pinecone, Weaviate, FAISS).•Experience in designing and scaling GenAI chatbots.•Experience in Agentic AI solutions. Good knowledge of Agentic AI frameworks (LangGraph, AutoGen, CrewAI ...

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 ...

knowledge of state of the art for ML Ops, ML infrastructure, including related tools, design patterns, best practices etc.* Experience with vector databases (e.g., Pinecone, FAISS, Milvus, Weaviate) and information retrieval systems and methods.* Familiarity with media content (video, audio) ML pipelines.* Proficiency in Python and common AI/ ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

skills Ability to translate complex technical concepts into business value Desirable Experience Advanced LLM techniques including agents and autonomous workflows Vector databases such as Pinecone, Weaviate or pgvector Docker, Kubernetes, ECS or containerised deployments Infrastructure as Code tools including Terraform or CloudFormation Large-scale data processing technologies such as Spark ...

LangGraph and agent orchestration frameworks. Desirable: Background in AI reasoning, planning, or multi-agent systems. Desirable: Familiarity with transformer architecture and vector database technologies (Pinecone, Weaviate, Chroma). Desirable: Contributions to open-source AI/agentic projects. Degree in a numerical degree preferred. What’s in it for you? Competitive ...

when non-AI approaches are more suitable Desirable Experience Advanced LLM techniques, including agents, tool use and agentic workflows Experience with vector databases (e.g. Pinecone, Weaviate, pgvector) Feature store technologies such as Feast or AWS Feature Store Containerisation and orchestration using Docker, Kubernetes or ECS Infrastructure as Code using Terraform ...

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 ...

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 ...

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

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

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 ...

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 ...

. Modern AI stack depth: Python/TypeScript, PyTorch, an orchestration framework (LangGraph, LangChain/LlamaIndex, CrewAI, or AutoGen), and vector databases (Pinecone, Qdrant, Weaviate, or Milvus) Model‐serving infrastructure: For example Triton/vLLM as well as LLM gateway products such as LiteLLM or Bifrost A production track record ...