18 of 18 Pinecone Jobs in the UK

integrating generative AI with enterprise applications using APIs, knowledge graphs, and orchestration tools. o Hands-on experience with various vector databases (eg, PG Vector, Pinecone, Mongo Atlas, Neo4j) for efficient data storage and retrieval. o Experience in dealing with large amounts of unstructured data and designing solutions for high-throughput ...

MLOps/LLMOps pipelines, and AI observability. Experience in Enterprise-grade RAG-based solutions with LLMs (OpenAI, Hugging Face, LLaMA, etc.) and vector databases (Pinecone, Weaviate, FAISS, etc.). Ability to design enterprise-level AI/Gen AI platform/solutions with the client's existing enterprise stack. Hands ...

production-ready AI systems. Experience in designing and implementing enterprise-grade AI solutions, including RAG-based solutions with LLMs and vector databases (e.g., Pinecone, Weaviate, FAISS). Proven experience in full stack development and AI/ML system implementation within enterprise environments. Strong grasp of advanced techniques such as complex ...

pipelines, and model monitoring practices Proven track record of delivering large-scale enterprise AI platforms Desirable Skills Experience working with vector databases such as Pinecone or FAISS Knowledge of AI governance frameworks, compliance standards, and security architecture Relevant certifications in Azure AI, AWS ML, or Kubernetes This opportunity is well ...

/GCP). Knowledge of MLOps workflows and ML tooling. Clear communication and a collaborative mindset. Nice‐to‐Haves Experience with LangChain, vector databases (Pinecone, Weaviate etc), or agent frameworks. Track record of advanced side projects or research contributions. Full stack familiarity (e.g., React, Postgres, TypeScript) is a plus. ...

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 ...

Agent Orchestration: LangChain, LangGraph, CrewAI - not just conceptual Agentic Coding Tools: Claude Code CLI, Cursor, OpenAI Codex, Copilot RAG & Vector Stores: Chroma, Weaviate, Pinecone, know where RAG breaks LLM APIs & SDKs: Anthropic, OpenAI, Gemini - prompt design, tool use Python/TypeScript: Primary languages for agent + backend development LangSmith/ ...

pipelines, eval tooling, guardrails, all of it. No handoffs, no red tape. You build it, you own it. Stack: LangChain/LangGraph, AWS Bedrock, Pinecone/FAISS/Weaviate, DeepEval/Langfuse, Docker, Python. Multimodal capability essential. What we're looking for 2+ years building and deploying production LLM systems ...

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 ...

environments Required Skills & Experience 4+ years in AI/ML engineering Strong Python Experience with LLMs and generative AI systems Experience with vector databases (Pinecone, Weaviate, FAISS, etc.) Experience building production AI systems Nice to Have Experience with LangChain/LlamaIndex or similar frameworks Knowledge of fine-tuning or prompt ...

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 ...

development and modern software architecture • Understanding of prompt design and managing AI-generated outputs • Ideally have experience in RAG pipelines and vector databases (e.g. Pinecone, Weaviate, pgvector) • Familiarity with cloud platforms is advantageous (AWS, Azure or GCP) • A proactive mindset with the ability to work effectively in a collaborative team ...

orchestration (LangGraph or similar). 🔍 You have strong RAG experience. Structuring unstructured data, making it queryable by LLMs, hands-on with vector databases (Pinecone, pgvector, or similar). 🏗️ You've designed and deployed API-first, event-driven architectures. You intuitively know how to build systems that scale. 🔭 You have experience ...

years focused on information retrieval, search systems, NLP, or RAG architectures. ● Deep expertise in vector databases — production experience with at least one of: Pinecone, Weaviate, Milvus, Qdrant, Chroma, pgvector, or Databricks Vector Search. Understanding of index types, distance metrics, sharding, and performance tuning. ● Hands-on experience with embedding models — OpenAI …/data product architectures in the context of serving retrieval use cases. Technical Stack ● Retrieval Orchestration LangGraph - LangChain, Pydantic.AI ● Vector Databases - Databricks Vector Search, Pinecone/Weaviate/Milvus/pgvector ● Knowledge Graphs - Neo4j, Amazon Neptune, or TigerGraph ● Data Platform - Databricks (Delta Lake, Unity Catalog, Spark SQL, MLflow) ● Embedding models ...

build systems that scale Experience building and shipping AI agents and LLM-powered systems in production Strong RAG experience; with hands on vector databases (Pinecone, pgvector or similiar) They are based in London with their engineering team operating either hybrid or remote. ⚡ This is a fantastic opportunity sitting right ...