1 to 25 of 26 Pinecone Jobs in the UK

Anthropic Claude, Azure OpenAI, and open-source alternatives (Llama, Mistral). Experience with prompt engineering, fine-tuning, RAG (Retrieval Augmented Generation) architectures, vector databases (Pinecone, ChromaDB, FAISS), embeddings, and building AI-powered automation solutions that leverage natural language understanding. Appian BPA Platform - Strong experience with Appian low-code platform including ...

Model Context Protocol (MCP). Knowledge of statistics, probability, and model evaluation techniques. experience with Retrieval-Augmented Generation (RAG) and vector databases like Pinecone or Weaviate. Proven track record of designing, developing, deploying, and managing AI/GenAI solutions in production. Additional Skills & Qualifications A broader understanding of machine learning ...

unsupervised) MLOps/LLMOps and AI observability Hands-on experience building enterprise RAG solutions using LLMs (e.g. OpenAI, Llama, Mistral, Claude) and vector databases (Pinecone, Weaviate, FAISS, etc.) Practical experience with GenAI frameworks such as LangChain, LlamaIndex, and agentic frameworks like AutoGen, CrewAI, LangGraph Strong Python expertise with AI/ ...

Hugging Face Inference Endpoints API Integration: OpenAI, Anthropic, Cohere, Mistral APIs LLM Frameworks: LangChain, LlamaIndex for building LLM-powered applications Vector Databases: FAISS, Weaviate, Pinecone, Qdrant (Nice-to-Have) Retrieval-Augmented Generation (RAG): Experience building hybrid systems combining LLMs with enterprise data MLOps & Infrastructure MLOps: Model versioning, monitoring, logging Bias ...

Claude, and Gemini . Implement RAG Pipelines Support the design and delivery of Retrieval-Augmented Generation (RAG) solutions using vector databases such as Pinecone or Weaviate . Develop Production-Ready Services Write clean, maintainable code in Python and/or JavaScript , contributing to microservices and APIs that meet performance, security ...

agent orchestration, memory, evaluation, and observability. Pioneer RAG & Multi-Modal Solutions Implement advanced Retrieval-Augmented Generation (RAG) pipelines using vector databases such as Pinecone and Weaviate . Build multi-modal workflows spanning text, voice, and video, with a strong focus on accuracy, explainability, and performance. Design data ingestion and enrichment ...

experience 6+ years of Python development with hands-on experience in Generative AI Strong experience with LLM APIs, prompt engineering, and vector databases (Pinecone, ChromaDB, FAISS) Proven team leadership and mentoring skills ; managing 3-5 engineers Cloud deployment experience with Docker/Kubernetes Deep understanding of transformer architectures, AI/ ...

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 ...

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 ...

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 ...

LangGraph, LangSmith or similar Solid NLP background (tokenisation, embeddings, transformers, BERT-style models, sentiment analysis) Experience integrating vector databases (e.g. Azure AI Search, OpenSearch, Pinecone, Weaviate) Cloud experience on Azure, AWS or GCP Familiarity with MLflow, model evaluation frameworks, observability & monitoring Strong understanding of deploying AI systems into real-world ...

workflows Designing and maintaining backend services and APIs (primarily Python, FastAPI/Flask) Building and scaling data pipelines and search systems using: ElasticSearch, Weaviate, Pinecone, and other vector databases Engineering secure, containerised architectures using Docker and Kubernetes Ensuring high availability, fault tolerance, and performance for mission-critical workloads Providing technical ...

workflows Designing and maintaining backend services and APIs (primarily Python, FastAPI/Flask) Building and scaling data pipelines and search systems using: ElasticSearch, Weaviate, Pinecone, and other vector databases Engineering secure, containerised architectures using Docker and Kubernetes Ensuring high availability, fault tolerance, and performance for mission-critical workloads Providing technical ...

experience with LangChain, LangGraph, and Indexify , with a deep understanding of RAG architectures . Expert-level SQL and experience with BigQuery and vector databases (Pinecone, Weaviate, Vertex AI Search). Proven track record in MLOps and deploying ML models at scale. Experience moving LLM-based prototypes into production environments with ...

experience with LangChain, LangGraph, and Indexify , with a deep understanding of RAG architectures . Expert-level SQL and experience with BigQuery and vector databases (Pinecone, Weaviate, Vertex AI Search). Proven track record in MLOps and deploying ML models at scale. Experience moving LLM-based prototypes into production environments with ...

production Strong Python development skills Hands-on experience with: Prompt engineering and evaluation Retrieval-Augmented Generation (RAG) Embeddings and vector databases (e.g. FAISS, Pinecone, Weaviate, Chroma) Experience building LLM-backed services using FastAPI/Flask or similar Strong understanding of trade-offs around accuracy, latency, cost and scalability Highly Desirable ...

engineering and chaining logic for AI-based tasks. Background in backend engineering (Python, NodeJS, or similar). Familiarity with tools like LangChain, OpenAI API, Pinecone, or similar . A problem-solver mindset—focused on delivering tangible outcomes using AI. Comfortable working in a fast-paced, agile environment. Excellent communication ...

REST APIs, JSON, and async patterns. Desirable skills/knowledge/experience Experience with vector databases (Cosmos DB with vector search, Redis Enterprise, or Pinecone) and semantic ranking. Knowledge of Azure Machine Learning for training/evaluation pipelines and model registries. Familiarity with Power Platform (AI Builder, Power Automate ...

systems: chunking strategies, document schemas, metadata, hybrid/dense retrieval, re-ranking, and grounding. Manage vector/keyword indexes (e.g., Azure AI Search, pgvector, Pinecone/Weaviate). Develop and deploy advanced NLP, information retrieval, and recommendation systems that enhance Chambers and Partners’ research and product offerings, including document understanding ...

LangChain, LangGraph, LlamaIndex, Semantic Kernel or similar. Optimize prompt strategies, memory, tools, and policies. · RAG & vector search: Architect robust RAG pipelines with vector DBs (Pinecone, Chroma, Weaviate, pgvector), including chunking, hybrid search, embeddings selection, caching, and evaluation. · Guardrails & observability: Implement policy/guardrails, safety filters, prompt/content validation … expertise with LLM orchestration frameworks (e.g., LangChain/LangGraph/LlamaIndex/Semantic Kernel). · Proven experience with RAG and vector databases (e.g., Pinecone, Chroma, Weaviate, pgvector). · Proficiency in Python (primary) and at least one of JavaScript/TypeScript or Java. · Solid foundation in cloud (AWS/GCP/ ...

LangChain, LangGraph, LlamaIndex, Semantic Kernel or similar. Optimize prompt strategies, memory, tools, and policies. RAG & vector search: Architect robust RAG pipelines with vector DBs (Pinecone, Chroma, Weaviate, pgvector), including chunking, hybrid search, embeddings selection, caching, and evaluation. Guardrails & observability: Implement policy/guardrails, safety filters, prompt/content validation … expertise with LLM orchestration frameworks (e.g.,LangChain/LangGraph/LlamaIndex/Semantic Kernel). Proven experience with RAG and vector databases (e.g., Pinecone, Chroma, Weaviate, pgvector). Proficiency in Python (primary) and at least one of JavaScript/TypeScript or Java. Solid foundation in cloud (AWS/GCP/ ...

LangChain, LangGraph, LlamaIndex, Semantic Kernel or similar. Optimize prompt strategies, memory, tools, and policies. RAG & vector search: Architect robust RAG pipelines with vector DBs (Pinecone, Chroma, Weaviate, pgvector), including chunking, hybrid search, embeddings selection, caching, and evaluation. Guardrails & observability: Implement policy/guardrails, safety filters, prompt/content validation … expertise with LLM orchestration frameworks (e.g.,LangChain/LangGraph/LlamaIndex/Semantic Kernel). Proven experience with RAG and vector databases (e.g., Pinecone, Chroma, Weaviate, pgvector). Proficiency in Python (primary) and at least one of JavaScript/TypeScript or Java. Solid foundation in cloud (AWS/GCP/ ...

embeddings, document chunking strategies, indexing, semantic search, and citation/grounding techniques. Experience with vector databases (e.g., Azure Cosmos DB vector search, Redis Enterprise, Pinecone) and reranking strategies. Experience with Git and CI/CD (Azure DevOps or GitHub), unit/integration testing for LLM pipelines, and environment/config ...