1 to 25 of 27 Pinecone Jobs in London

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 ...

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/ ...

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/ ...

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 ...

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 ...

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 ...

graphs for context enrichment, reasoning, and workflow automation RAG & Knowledge Systems: End‐to‐end RAG pipelines using enterprise search + vector stores (e.g., Elastic, Pinecone) with grounding, evaluation, and optimization Model Lifecycle & Governance: Model evaluation, monitoring, prompt/version control, and Responsible AI/MRM compliance Enterprise AI Integration & Data ...

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 continuous integration and deployment tools such as GitLab, GitHub, or Jenkins.Database ManagementVector 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 ControlProficient in Git and version control platforms ...

Large Language Models (LLMs)Prompt engineering, fine-tuning and Retrieval-Augmented Generation (RAG) LangChain, LangGraph or similar agent frameworks Vector databases such as Pinecone, Chroma or FAISS AI Agents and Generative AI applications Cloud platforms including AWS and/or Azure Modern ML pipelines and MLOps practices Agile delivery methodologies ...

Computer Science, Data Science, or related field Nice to have Experience with Azure AI Agent Service or Microsoft Agent Framework Familiarity with vector databases (Pinecone, Weaviate, Qdrant, Milvus) Knowledge of AI safety techniques such as guardrails, bias mitigation, and model explainability Understanding of Intelligent Document Processing, data lineage, and distributed ...

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 ...

/ML concepts and protocols, including Retrieval-Augmented Generation (RAG), agentic system architectures, and Model Context Protocol (MCP) Exposure to vector stores such as Pinecone, GCP RAG engine, and AWS S3 Vector Buckets Previous experience deploying and managing ML models Experience working in highly regulated environments or industries We recognize ...

model and data security posture (AI-SPM/DSPM concepts). Familiarity with the Model Context Protocol (MCP), agent runtimes, or vector databases (e.g., Pinecone, Milvus, Weaviate, Chroma). Background in enterprise data governance, security, backup/resilience, or the Microsoft 365/multi-cloud ecosystem where AvePoint operates. Experience ...

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 ...

also have experience working with technologies such as OpenAI, Azure OpenAI, Hugging Face, Llama or similar Large Language Models, alongside vector databases including Pinecone, Weaviate or FAISS. Experience designing AI solutions across Azure, AWS or Google Cloud would be highly beneficial. Most importantly, you'll be an excellent communicator ...

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 a big advantage. ...

practices, ideally in a regulated environment Preferred Qualifications Background in financial services or another regulated enterprise environment Experience with vector databases (for example pgvector, Pinecone, Weaviate, or Chroma) and agent or orchestration frameworks (for example LangChain, LlamaIndex, or the Model Context Protocol) Experience with MLOps/LLMOps tooling such ...

tasks reliably and safely. Retrieval‐Augmented Generation (RAG) & Knowledge Systems : Proven experience designing RAG and knowledge‐grounded systems, including chunking strategies, embeddings, vector databases (Pinecone, Weaviate, Chroma, pgvector, FAISS), hybrid search, reranking, and evaluation of retrieval quality. Familiarity with advanced patterns such as GraphRAG and agentic RAG to reduce hallucination … driven and orchestration patterns Cloud AI platforms & model hosting: Amazon Bedrock, Azure OpenAI/AI Foundry, Google Vertex AI, Hugging Face Vector databases & retrieval: Pinecone, Weaviate, Chroma, pgvector, FAISS; embeddings, semantic and hybrid search, reranking MLOps/LLMOps & deployment: Docker, Kubernetes, FastAPI, CI/CD; observability, tracing, evaluation tooling (LangSmith ...

practices, ideally in a regulated environment. Preferred qualifications Background in financial services or another regulated enterprise environment. Experience with vector databases (for example pgvector, Pinecone, Weaviate, or Chroma) and agent or orchestration frameworks (for example LangChain, LlamaIndex, or the Model Context Protocol). Experience with MLOps/LLMOps tooling such ...

GenAI & RAG Expertise: 2+ years of hands‐on experience building and productionising LLM applications, with deep technical knowledge of vector databases (e.g., Qdrant, Weaviate, Pinecone, pgvector) and orchestration layers (e.g., LangGraph, LlamaIndex). Comfortable working with heterogeneous documents like pdfs. Experience working with re‐ranking models. Production-Grade Asynchronous Python ...

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. ...