24 of 24 Pinecone Jobs in the UK

experience with GenAI platforms: OpenAI, Azure OpenAI, LangChain, or similar frameworks Experience building RAG applications with chunking, vectorisation, retrieval strategies Vector databases: pgvector, Pinecone, Weaviate, or similar DevOps maturity: Infrastructure as Code (Terraform, Bicep, ARM templates), advanced CI/CD Containerisation and orchestration: Docker and Kubernetes (AKS) Database expertise: PostgreSQL ...

frameworks and orchestration AI/ML Engineering Python, PyTorch, TensorFlow, JAX NLP, deep learning, model optimisation Evaluation frameworks and guardrails Data & Platforms Vector databases (Pinecone, Weaviate, FAISS, Milvus) Knowledge graphs and semantic search Data engineering pipelines MLOps & Deployment CI/CD for ML, model monitoring, versioning Kubernetes, Docker, serverless architectures ...

/ML platforms such as Azure ML, AWS SageMaker, Vertex AI, Databricks, Modal, and Fly.io. Deploy and manage vector databases and embedding stores, including Pinecone, Weaviate, Milvus, FAISS, ChromaDB, and pgVector. Implement LLMOps/PromptOps practices using tools such as: Weights & Biases, MLflow, LangSmith, LangFuse, PromptLayer, Humanloop, Helicone, Arize Phoenix ...

/ML platforms such as Azure ML, AWS SageMaker, Vertex AI, Databricks, Modal, and Fly.io. Deploy and manage vector databases and embedding stores, including Pinecone, Weaviate, Milvus, FAISS, ChromaDB, and pgVector. Implement LLMOps/PromptOps practices using tools such as: Weights & Biases, MLflow, LangSmith, LangFuse, PromptLayer, Humanloop, Helicone, Arize Phoenix ...

such as GPT, Claude, Gemini as well as self-hosted LLMs along with MCP integrations Implement Retrieval-Augmented Generation (RAG) techniques leveraging vector databases (Pinecone/ChromaDB/Weaviate/pgvector/etc), search engines such as ElasticSearch/Solr using both TF/IDF BM25 based full text search ...

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 ...

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 ...

Create front-end applications with React, TypeScript, and frameworks like Next.js or Vite. Integrate LLMs (e.g., OpenAI, Anthropic, Mistral) and vector databases (e.g., ChromaDB, Pinecone, PGVector). Deploy solutions using AWS or Azure, Docker, Kubernetes, and Terraform. Implement CI/CD pipelines and monitor LLM performance using tools like Langsmith ...

system architecture, including microservices, event-driven patterns, RAG, Graph RAG, and multi-agent systems.Vector Databases & Embeddings: Experience with embedding models and vector databases (e.g., Pinecone, Weaviate, Chroma, FAISS).Advanced AI Concepts: Complex task decomposition for agents, reasoning engines, knowledge graphs, autonomous agent design, and evaluation methodologies for AI systems.Software Engineering ...

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 ...

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 ...

experiment tracking, prompt/version control, cost/latency optimization; Tools: serverless AWS, LangChain/LangGraph, OpenAI/Anthropic/Azure OpenAI; vector DBs (Pinecone/FAISS/Milvus) We balance exploration with delivery: test ideas quickly, then productionize what works. “Done” means quality goals are met; then we keep ...

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 ...

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 ...

Bring Technical Excellence: Deep expertise in Python and frameworks like LangChain , LlamaIndex , or Haystack . Vector Expertise: Proven experience with vector databases such as Pinecone, Weaviate, or Milvus . Cloud Architecture: Strong proficiency in deploying AI solutions within AWS or Azure ecosystems. Industry Context: (Bonus) A background in FinTech ...

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 ...

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 ...

Stack: Deep expertise in Google Cloud Platform (GCP) , Vertex AI , and Gemini Models . AI Frameworks: Strong hands-on experience with LangChain , Vector Databases (Pinecone, Weaviate, etc.), and LLMOps tools. Domain: Experience delivering AI/GenAI use cases within Banking or highly regulated industries is a significant plu Why Apply ...

Lead the development of Foundational Semantic Ontologies that allow AI models to reason across disparate chemical data types. Design Vector Database integrations (e.g., pgvector, Pinecone) to facilitate similarity searches across billions of chemical entities. Industrial Telemetry & Edge Synchronization Architect the ingestion of high-frequency robot and sensor telemetry using MQTT … generating very large volumes of time-series data. Hands-on understanding of stream ingestion patterns (MQTT). Experience with graph or Vector databases ( Neo4j, Pinecone, pgvector) and modelling complex, highly relational domains. Proven experience designing distributed data systems across multiple services, teams, or locations. Demonstrable experience building impactful solutions with ...