1 to 25 of 28 Pinecone Jobs in the UK

strong exposure to Python and common AI libraries (PyTorch, TensorFlow). Familiarity with: LLMs (OpenAI, Anthropic, Hugging Face, LLaMA models) Vector databases (Pinecone, Weaviate, FAISS , Qudrant) Agentic AI frameworks (exposure to LangGraph, AutoGen, CrewAI or others) Exposure to cloud AI platforms (Azure AI Foundry, AWS Bedrock/SageMaker, GCP Vertex ...

Face, LangChain) Oversee integration of LLMs (OpenAI, Anthropic, Gemini, Mistral) via enterprise platforms (Azure OpenAI, Vertex AI) Implement RAG architectures and manage vector databases (Pinecone, Weaviate, FAISS, Milvus) to enable enterprise knowledge solutions Data & Engineering Excellence Lead the evolution of modern, enterprise-scale data platforms (Databricks, Snowflake, Synapse, BigQuery) Ensure ...

cross-functional teams within a fast-paced environment Nice to Have Experience within financial services or other regulated industries Exposure to vector databases (e.g. Pinecone, Weaviate, FAISS) Experience with MLOps/LLMOps and deploying models into production Familiarity with LLM fine-tuning, evaluation, or guardrailing techniques Experience building internal tools ...

proficiency in Python , PyTorch/TensorFlow, and GenAI frameworks like LangChain, LlamaIndex, or CrewAI . Data Architecture: Hands-on experience with Vector Databases (e.g., Pinecone, Milvus, Weaviate) and SQL/NoSQL systems. Infrastructure: Proven track record in MLOps , containerization (Docker/K8s), and cloud platforms (Azure/AWS). Ethical ...

proficiency in Python , PyTorch/TensorFlow, and GenAI frameworks like LangChain, LlamaIndex, or CrewAI . Data Architecture: Hands-on experience with Vector Databases (e.g., Pinecone, Milvus, Weaviate) and SQL/NoSQL systems. Infrastructure: Proven track record in MLOps , containerization (Docker/K8s), and cloud platforms (Azure/AWS). Ethical ...

Implementing advanced RAG pipelines hybrid search, re-ranking, query rewriting, context compression, evaluation and grounding. Working with vector stores such as Azure AI Search, Pinecone, Qdrant, Weaviate and Chroma, and tuning embedding models for enterprise data. Building agentic systems using frameworks like LangGraph, Semantic Kernel, LangChain, LlamaIndex and AutoGen tool ...

Implementing advanced RAG pipelines hybrid search, re-ranking, query rewriting, context compression, evaluation and grounding. Working with vector stores such as Azure AI Search, Pinecone, Qdrant, Weaviate and Chroma, and tuning embedding models for enterprise data. Building agentic systems using frameworks like LangGraph, Semantic Kernel, LangChain, LlamaIndex and AutoGen tool ...

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 ...

environments. Strong expertise in Python and AI/ML libraries: PyTorch, TensorFlow, Scikit‐Learn, Keras, NumPy, Pandas, JAX, XGBoost, PyTorch Geometric, OpenCV, Transformers, LangChain, Pinecone . Proven hands‐on experience deploying models in production and building scalable AI software. Deep understanding of advanced modelling methods: deep learning, GNNs, computer vision ...

Skills Python, TypeScript LLM frameworks (LangChain, LlamaIndex, OpenAI tools, Semantic Kernel) Vector databases (Pinecone, Weaviate, Chroma) Cloud (AWS/Azure/GCP) Docker, Kubernetes CI/CD, observability, testing for AI systems Experience Strong experience building LLM applications, RAG systems, or AI agents Understanding of prompt engineering, tool-calling ...

connect multiple services Good communication skills and ability to work with non-technical stakeholders Desired Skills Experience with RAG architectures and vector databases (e.g. Pinecone, FAISS, Azure AI Search) Experience deploying applications on Azure Understanding of CI/CD and software engineering best practices Experience building workflow automation systems Familiarity ...

leveraging AI/GAI technologies and large language models (LLMs) Advanced AI Integration : Apply experience with retrieval-augmented generation (RAG), vector databases (e.g. Pinecone, Weaviate, FAISS), and enterprise search for AI-driven knowledge discovery Optimize AI Performance : Utilize practical experience designing structured prompts, fine-tuning models, and cost optimization strategies ...

LangChain, CrewAI) in production. Strong Python engineering skills with solid testing, optimisation, CI/CD, and code quality; Experience implementing and scaling vector databases (Pinecone, Weaviate, Milvus) for retrieval and reasoning workloads. Deep expertise in cloud‐native AI engineering on AWS, with Azure knowledge and ability to design distributed, fault ...

forward deployed roles Strong Python Experience building and deploying LLM applications (OpenAI, Anthropic, Gemini, etc.) Deep familiarity with RAG methodologies, embeddings, and vector databases (Pinecone, Weaviate, pgvector) Robust API integration experience, including working with third-party datasets, web APIs, or scrapers A product mindset, enjoys crafting scrappy prototypes that evolve ...

Knowledge of prompt engineering and optimization techniques C#/.NET background for enterprise integration in financial services Experience with RAG pipelines and vector databases (Pinecone, Weaviate, ChromaDB, etc.) Understanding of embedding models and semantic search Knowledge of fine-tuning and model customization approache Experience working for Financial Services companies ...

forward deployed roles Strong Python Experience building and deploying LLM applications (OpenAI, Anthropic, Gemini, etc.) Deep familiarity with RAG methodologies, embeddings, and vector databases (Pinecone, Weaviate, pgvector) Robust API integration experience, including working with third-party datasets, web APIs, or scrapers A product mindset, enjoys crafting scrappy prototypes that evolve ...

forward deployed roles Strong Python Experience building and deploying LLM applications (OpenAI, Anthropic, Gemini, etc.) Deep familiarity with RAG methodologies, embeddings, and vector databases (Pinecone, Weaviate, pgvector) Robust API integration experience, including working with third-party datasets, web APIs, or scrapers A product mindset, enjoys crafting scrappy prototypes that evolve ...

frameworks (CrewAI, AutoGen); Familiarity with AI security tools: Garak, Rebuff, NeMo Guardrails (NVIDIA), Prompt Guard, LLM Guard, Lakera Guard; Experience with vector database security: Pinecone, Weaviate, ChromaDB, pgvector access control and data isolation; Knowledge of emerging AI standards: MCP (Model Context Protocol), Agent‐to‐Agent (A2A) Protocol, and AI gateway ...

Foundry, App Services, Container Apps, VNet peering) and/or AWS (Bedrock, ECS, Lambda) applied in real deployments. → Vector databases and advanced RAG architectures (Pinecone, CosmosDB Vector, or Qdrant), including chunking strategies and embedding model selection. We need someone who can thoughtfully design and debate these architectures with the team ...

MongoDB/DynamoDB) Experience with CI/CD, microservices, TDD/BDD. Knowledge of secure system design. Desirable (AI & Data) Vector DBs: Milvus, Weaviate, Pinecone Data orchestration: Airflow, Prefect, Dagster Search: ElasticSearch/OpenSearch AI frameworks: LangChain, Hugging Face MLOps: MLflow, Kubeflow If you are looking for an opportunity ...

MongoDB/DynamoDB) Experience with CI/CD, microservices, TDD/BDD. Knowledge of secure system design. Desirable (AI & Data) Vector DBs: Milvus, Weaviate, Pinecone Data orchestration: Airflow, Prefect, Dagster Search: ElasticSearch/OpenSearch AI frameworks: LangChain, Hugging Face MLOps: MLflow, Kubeflow If you are looking for an opportunity ...

similar. Experience working with Generative AI and ML infrastructure, including: Fine-tuning transformer models Managing embeddings Building RAG pipelines Familiarity with vector databases (e.g., Pinecone, Milvus, Weaviate) and semantic search techniques. Strong foundation in cloud infrastructure, networking, security, CI/CD pipelines, and observability. Experience with cloud platforms ...

execute multi-step tasks. The Data Architect: Proficiency in Vector Databases is essential. You should be comfortable designing data persistence layers using PG Vector, Pinecone, Milvus, or Mongo Atlas to handle large amounts of unstructured data. The MLOps Engineer: You don't just write code; you ship it. Our client ...

queuing (Celery, RabbitMQ, SQS) Event-driven architecture CI/CD pipelines What You'll Work With Python backend services LLM orchestration layers Vector databases (Pinecone, pgvector or similar) API integrations (CRMs, property systems) TypeScript React Next.js Nice to Haves Voice and telephony systems (Twilio, SIP, WebRTC) STT/TTS pipelines ...