1 to 25 of 37 pgvector Jobs in England

consistent operation. Retrieval‐Augmented Generation (RAG) & Knowledge Architecture – expertise in RAG and knowledge‐grounded systems, including chunking, embeddings, vector databases (Pinecone, Weaviate, Chroma, pgvector, FAISS), hybrid search and retrieval evaluation. Familiarity with GraphRAG and agentic RAG. LLMOps, Evaluation & Responsible AI – operationalizing LLM and agentic systems at scale; evaluation harnesses, quality ...

OpenAI, Anthropic, Mistral, Llama and similar LLMs Use LangChain, LangGraph, CrewAI or similar AI framework Work with vector databases including Pinecone, Qdrant, ChromaDB and PGVector Take GenAI POCs into production and scale them Build APIs, microservices and AI integrations Deploy solutions using AWS/Azure, Docker and Kubernetes Write clean ...

OpenAI, Anthropic, Mistral, Llama and similar LLMs Use LangChain, LangGraph, CrewAI or similar AI framework Work with vector databases including Pinecone, Qdrant, ChromaDB and PGVector Take GenAI POCs into production and scale them Build APIs, microservices and AI integrations Deploy solutions using AWS/Azure, Docker and Kubernetes Write clean ...

integration and deployment tools such as **GitLab**, **GitHub**, or **Jenkins**.## **Database Management*** 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.## **Version Control*** Proficient ...

integration and deployment tools such as **GitLab**, **GitHub**, or **Jenkins**.## **Database Management*** 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.## **Version Control*** Proficient ...

continuous integration and deployment tools such as GitLab, GitHub, or Jenkins. Database Management 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. Version Control Proficient ...

OpenAI, Anthropic, Mistral, Llama and similar LLMs Use LangChain, LangGraph, CrewAI or similar AI frameworks Work with vector databases including Pinecone, Qdrant, ChromaDB and PGVector Take GenAI POCs into production and scale them Build APIs, microservices and AI integrations Deploy solutions using AWS/Azure, Docker and Kubernetes Write clean ...

OpenAI, Anthropic, Mistral, Llama and similar LLMs Use LangChain, LangGraph, CrewAI or similar AI frameworks Work with vector databases including Pinecone, Qdrant, ChromaDB and PGVector Take GenAI POCs into production and scale them Build APIs, microservices and AI integrations Deploy solutions using AWS/Azure, Docker and Kubernetes Write clean ...

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 ...

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 ...

Build high-performance APIs and caching strategies enabling low‐latency data access for AI agents and orchestration systems. Implement vector-based data retrieval layers (pgVector, Pinecone) and ensure efficient embedding pipelines for AI contexts. Partner with AI teams to monitor data latency, cost efficiency, and observability metrics. Collaboration & Governance Partner ...

approaches are more suitable Desirable Experience Advanced LLM techniques, including agents, tool use and agentic workflows Experience with vector databases (e.g. Pinecone, Weaviate, pgvector) Feature store technologies such as Feast or AWS Feature Store Containerisation and orchestration using Docker, Kubernetes or ECS Infrastructure as Code using Terraform or CloudFormation Large ...

platforms and scalable pipelines. Excellent knowledge of PostgreSQL (or similar relational databases) and NoSQL databases. Experience with vector databases such as Qdrant, Milvus or pgvector . Familiarity with technologies such as Apache Spark, Airflow, Kafka, Elasticsearch/OpenSearch, Pandas and Polars . Strong understanding of data modelling, storage architecture ...

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 Python skills ...

Azure)* CI/CD pipelines* Scalable service architectureData and Retrieval Systems* Experience building and operating knowledge layers* Vector databases (e.g. Pinecone, Weaviate, pgvector)* Document ingestion pipelines* Embedding workflows* Search and retrieval optimization**Nice to Have Experience with:*** MCP architectures or tool-connected AI systems* Agent frameworks* Knowledge graph systems* Streaming ...

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 Python skills ...

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

Agent Framework Knowledge of MCP and A2A protocols for agent and tool interoperability Hands-on work with vector databases like Pinecone, Weaviate, Qdrant or pgvector Familiarity with distributed systems, workflow engines (Temporal, Airflow or Dagster) and event-driven architectures Experience with open-source LLMs or Small Language Models for custom ...

/functions callable by AI agents (tool schemas, function calling, structured outputs). Experience with retrieval-augmented generation (RAG) : vector databases (e.g., Pinecone, Weaviate, pgvector), embeddings, and chunking strategies. Working knowledge of prompt engineering and evaluation techniques for agent reliability, safety, and cost control. Familiarity with orchestrating multi-agent workflows ...

like Llama/Mistral) and orchestration frameworks (LangChain, LlamaIndex, Semantic Kernel, or equivalent). Practical experience with RAG, embeddings, and vector databases (Pinecone, Weaviate, pgvector, Azure AI Search). Familiarity with agentic architectures, function/tool calling, and structured outputs. Prompt engineering and evaluation experience, with awareness of guardrails ...

emphasis on Python development in production environments Proven expertise in building and deploying generative AI applications, leveraging LLMs, vector databases like Pinecone, Weaviate, or pgvector, and modern open-source agentic frameworks Practical experience with microservices architecture, RESTful APIs, cloud platforms such as AWS, GCP, or Azure, and containerization with Docker ...

like Llama/Mistral) and orchestration frameworks (LangChain, LlamaIndex, Semantic Kernel, or equivalent). Practical experience with RAG, embeddings, and vector databases (Pinecone, Weaviate, pgvector, Azure AI Search). Familiarity with agentic architectures, function/tool calling, and structured outputs. Prompt engineering and evaluation experience, with awareness of guardrails ...

LangChain, CrewAI, Agentforce or similar Foundation model providers: Claude Code/Codex/Gemini, OpenAI or AWS Bedrock Vector databases: Pinecone, Weaviate, LlamaIndex or pgvector Cloud platforms: AWS Bedrock, GCP Vertex AI or Azure AI Studio CI/CD for AI: version-controlled prompts, automated testing, deployment pipelines ...

etc.) critically and effectively as part of their day-to-day workflow. Bonus points for: Experience with retrieval-augmented generation (RAG) and vector databases (pgvector, Pinecone, or similar). Experience designing multi-agent systems and agent orchestration patterns. Familiarity with LLM observability tools (LangSmith, Langfuse, Arize, or similar). Experience ...

LangChain, CrewAI, Agentforce or similar Foundation model providers: Claude Code/Codex/Gemini, OpenAI or AWS Bedrock Vector databases: Pinecone, Weaviate, LlamaIndex or pgvector Cloud platforms: AWS Bedrock, GCP Vertex AI or Azure AI Studio CI/CD for AI: version-controlled prompts, automated testing, deployment pipelines ...