1 to 25 of 54 Pinecone Jobs in the UK

with Generative AI, LLMs (such as GPT, Claude, and Llama), and prompt engineering. Strong knowledge of RAG, embeddings, and vector databases (such as FAISS, Pinecone, ChromaDB, or Weaviate). Experience with LangChain, LangGraph, Semantic Kernel, or similar frameworks. Solid understanding of NLP, machine learning, and deep learning concepts. Hands ...

delivery environments.Generative AI & LLMs: OpenAI/Azure OpenAI APIs Prompt Engineering RAG (Retrieval Augmented Generation) LangChain/LangGraph AI Agents Vector Databases (FAISS, ChromaDB, Pinecone anyone they can learn and come) FastAPI-based AI services LLM Evaluation and Testing Nice to have React, Azure, AWS, Power BI, automation tools such ...

delivery environments.Generative AI & LLMs: OpenAI/Azure OpenAI APIs Prompt Engineering RAG (Retrieval Augmented Generation) LangChain/LangGraph AI Agents Vector Databases (FAISS, ChromaDB, Pinecone anyone they can learn and come) FastAPI-based AI services LLM Evaluation and Testing Nice to have React, Azure, AWS, Power BI, automation tools such ...

have experience with: Agentic AI and multi-agent systems. LangChain, LangGraph or similar orchestration frameworks. Retrieval-Augmented Generation (RAG). Vector Databases (pgvector, Pinecone, Weaviate, Milvus, etc.). Model Context Protocol (MCP). FastAPI or modern Python backend frameworks. CI/CD and MLOps practices. Building production AI systems ...

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 ...

Experience with continuous integration and deployment tools such as GitLab, GitHub, or Jenkins. 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. Proficient in Git and version ...

Experience with continuous integration and deployment tools such as GitLab, GitHub, or Jenkins. 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. Proficient in Git and version ...

with LLM APIs and frameworks (e.g. OpenAI/Anthropic SDKs, LangChain, LlamaIndex, or similar) Solid understanding of RAG architectures, embeddings, and vector databases (pgvector, Pinecone, Weaviate, Qdrant, or similar) Experience building APIs with FastAPI or Django; async Python is a plus Strong PostgreSQL skills; pgvector experience is a plus Familiarity ...

scikit-learn; DL frameworks TensorFlow/PyTorch). Experience with LLM/RAG toolchains (e.g., LangChain, LlamaIndex, Semantic Kernel) and vector search (e.g., Pinecone, Weaviate, FAISS, Azure AI Search). Hands‐on experience with AWS Bedrock and Sagemaker would be highly desirable Experience with GenAI platforms (e.g., OpenAI API, Anthropic ...

Claude Code, Cursor, GitHub Copilot) to accelerate software solution development in production environments. Hands-on experience with modern AI infrastructure, including vector databases (e.g., Pinecone, Weaviate, Qdrant), cloud platforms (Azure, AWS, or GCP), API design, and containerized deployment (Docker, Kubernetes). Experience designing data pipelines and document processing systems ...

similar.* CI/CD: Comfortable owning pipelines end to end (GitHub Actions, GitLab CI, Jenkins).* Database Management: Experience with vector databases (ChromaDB, Pinecone, PGVector, Qdrant, MongoDB Vector Search); familiarity with NoSQL (MongoDB preferred) and SQL (PostgreSQL) databases.**Commercial and Stakeholder Skills*** Commercial awareness: able to reason about effort, scope ...

similar.* CI/CD: Comfortable owning pipelines end to end (GitHub Actions, GitLab CI, Jenkins).* Database Management: Experience with vector databases (ChromaDB, Pinecone, PGVector, Qdrant, MongoDB Vector Search); familiarity with NoSQL (MongoDB preferred) and SQL (PostgreSQL) databases.**Commercial and Stakeholder Skills*** Commercial awareness: able to reason about effort, scope ...

similar.* CI/CD: Comfortable owning pipelines end to end (GitHub Actions, GitLab CI, Jenkins).* Database Management: Experience with vector databases (ChromaDB, Pinecone, PGVector, Qdrant, MongoDB Vector Search); familiarity with NoSQL (MongoDB preferred) and SQL (PostgreSQL) databases.**Commercial and Stakeholder Skills*** Commercial awareness: able to reason about effort, scope ...

similar. CI/CD: Comfortable owning pipelines end to end (GitHub Actions, GitLab CI, Jenkins). Database Management: Experience with vector databases (ChromaDB, Pinecone, PGVector, Qdrant, MongoDB Vector Search); familiarity with NoSQL (MongoDB preferred) and SQL (PostgreSQL) databases. Commercial and Stakeholder Skills Commercial awareness: able to reason about effort, scope ...

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 ...

help you with them: Experience with advanced LLM techniques: agents, tool use, and agentic workflows Experience with vector databases (Pinecone, Weaviate, pgvector) for RAG applications Experience with feature stores (Feast, AWS Feature Store) Experience with containerisation (Docker) and orchestration (Kubernetes, ECS) Familiarity with Infrastructure as Code (Terraform, CloudFormation) Experience with ...

Gemini, open‐weight models) with tools, data, and external systems through MCP and custom connectors. Apply RAG techniques where they actuallyhelp:vector databases (Pinecone, Chroma,Weaviate,pgvector), hybrid retrieval withElasticSearchorSolr, and BM25 + similarity search. Work across relational, document, key‐value, and graph stores as the problem demands; use event ...

these, but if not well help you with them: Experience with advanced LLM techniques: agents, tool use, and agentic workflows Experience with vector databases (Pinecone, Weaviate, pgvector) for RAG applications Experience with feature stores (Feast, AWS Feature Store) Experience with containerisation (Docker) and orchestration (Kubernetes, ECS) Familiarity with Infrastructure ...

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 ...

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 ...

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 ...

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 ...

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 ...

approach to the software development lifecycle (SDLC). Desirable: AI & Data Underpinnings Vector Databases: Experience with high-dimensional data retrieval using Milvus, Weaviate, or Pinecone (essential for RAG architectures). Data Orchestration: Familiarity with Airflow, Prefect, or Dagster for managing complex data movement and model training pipelines. Search & Discovery: Advanced ...