16 of 16 Pinecone Jobs in the UK excluding London

delivery environments.Generative AI & LLMs: OpenAI/Azure OpenAI APIs Prompt Engineering RAG (Retrieval Augmented Generation) LangChain/LangGraph AI Agents Vector Databases (FAISS, ChromaDB, Pinecone anyone they can learn and come) FastAPI-based AI services LLM Evaluation and Testing Nice to have React, Azure, AWS, Power BI, automation tools such ...

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 ...

similar.* CI/CD: Comfortable owning pipelines end to end (GitHub Actions, GitLab CI, Jenkins).* Database Management: Experience with vector databases (ChromaDB, Pinecone, PGVector, Qdrant, MongoDB Vector Search); familiarity with NoSQL (MongoDB preferred) and SQL (PostgreSQL) databases.**Commercial and Stakeholder Skills*** Commercial awareness: able to reason about effort, scope ...

similar.* CI/CD: Comfortable owning pipelines end to end (GitHub Actions, GitLab CI, Jenkins).* Database Management: Experience with vector databases (ChromaDB, Pinecone, PGVector, Qdrant, MongoDB Vector Search); familiarity with NoSQL (MongoDB preferred) and SQL (PostgreSQL) databases.**Commercial and Stakeholder Skills*** Commercial awareness: able to reason about effort, scope ...

similar. CI/CD: Comfortable owning pipelines end to end (GitHub Actions, GitLab CI, Jenkins). Database Management: Experience with vector databases (ChromaDB, Pinecone, PGVector, Qdrant, MongoDB Vector Search); familiarity with NoSQL (MongoDB preferred) and SQL (PostgreSQL) databases. Commercial and Stakeholder Skills Commercial awareness: able to reason about effort, scope ...

GitLab, Jenkins, or similar. Familiarity with monitoring and observability tools for AI applications and services. Database Technologies Experience with vector databases such as ChromaDB, Pinecone, PGVector, Qdrant, MongoDB, or similar solutions. Familiarity with NoSQL databases. Experience working with SQL databases, particularly PostgreSQL or equivalent. Version Control Strong experience using ...

these, but if not well help you with them: Experience with advanced LLM techniques: agents, tool use, and agentic workflows Experience with vector databases (Pinecone, Weaviate, pgvector) for RAG applications Experience with feature stores (Feast, AWS Feature Store) Experience with containerisation (Docker) and orchestration (Kubernetes, ECS) Familiarity with Infrastructure ...

approach to the software development lifecycle (SDLC). Desirable: AI & Data Underpinnings Vector Databases: Experience with high-dimensional data retrieval using Milvus, Weaviate, or Pinecone (essential for RAG architectures). Data Orchestration: Familiarity with Airflow, Prefect, or Dagster for managing complex data movement and model training pipelines. Search & Discovery: Advanced ...

e.g. NeMo Guardrails, OpenTelemetry GenAI conventions, LangSmith, Braintrust)MLOps & LLMOps• Hands-on with MLOps platforms (Azure ML, Databricks, SageMaker) and vector/retrieval databases (Pinecone, Milvus, pgvector)• Experience with GPU-accelerated infrastructure and NVIDIA AI Enterprise or equivalent stacks• Exposure to fine-tuning, RLHF, or SLM distillation is a strong ...

inference-cost optimisation Scalable cloud-based AI deployment Experience with technologies such as LangGraph, LangChain, LlamaIndex, AutoGen, Google Vertex AI, Gemini, BigQuery, Qdrant, ChromaDB, Pinecone, Weaviate or Milvus would be valuable. Network Programmability Hands-on network programmability experience is not essential , but you should understand the technologies and tools likely ...

your own) and a clear view on when agents are the right tool versus when they’re overkill Comfortable working with vector stores (Pinecone, Weaviate, Chroma, pgVector, or similar) Solid software engineering fundamentals — testing, CI/CD, observability — applied to non-deterministic systems Comfortable in client‐facing settings, including running ...

production as APIs or services, with attention to latency, cost, scalability, and reliability Design and implement RAG (Retrieval‐Augmented Generation) systems using vector databases (Pinecone, Weaviate, Chroma), including embedding, chunking, and retrieval‐quality evaluation Integrate LLM APIs (OpenAI, Anthropic, etc.) into production services and product workflows Design and build agentic … OpenAI, Anthropic; LangChain or LlamaIndex Agentic AI – LangGraph, LangChain Agents, AutoGen, or CrewAI; tool/function calling, orchestration, memory, and guardrails RAG & vector databases —-Pinecone, Weaviate, or Chroma Databases – PostgreSQL, MongoDB, or Firebase Cloud & deployment – AWS, GCP, or Azure; Docker; CI/CD Security & compliance – secure coding, secrets management, access ...

operating knowledge graphs or graph databases (e.g., Jena Fuseki, Neo4j, Amazon Neptune, or equivalent). Experience with vector databases and embedding pipelines (e.g., Pinecone, Weaviate, Qdrant, pgvector). Practical experience implementing RAG architectures or LLM-integrated data pipelines. Familiarity with semantic web standards—JSON-LD, RDF, OWL, or SKOS. Strong ...

Qualifications Experience with Digital Twin platforms Experience with Knowledge Graph implementations Data Mesh architectures LangChain, LangGraph and LlamaIndex Vertex AI and Gemini Vector databases (Pinecone, Weaviate, Milvus, Qdrant) Kubernetes and GKE Autonomous Network and AI-Ops programmes If you're excited about this role but don’t meet every requirement ...

/Scala, Kafka, Pulsar, Azure Event Hub, Collibra, Apache Iceberg, Apache Arrow, PySpark or AI engineering technologies such as Snowflake AI, LangChain, LlamaIndex or Pinecone would be advantageous. This is a great opportunity to join a collaborative team and have genuine influence over the development of a modern data platform ...

data platformsTelecom Domain ExperienceNice-to-Have QualificationsExperience with Digital Twin platformsExperience with Knowledge Graph implementationsData Mesh architecturesLangChain, LangGraph and LlamaIndexVertex AI and GeminiVector databases (Pinecone, Weaviate, Milvus, Qdrant)Kubernetes and GKEAutonomous Network and AI-Ops programmesIf you're excited about this role but don’t meet every requirement, we still ...