1 to 25 of 43 Permanent pgvector Jobs in the UK

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 ...

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 ...

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 ...

capabilities and agentic workflows into full-stack applications. Familiarity with Strands Agents, MCP, and multi-agent workflows. Experience with vector databases such as pgvector, OpenSearch, Pinecone, or equivalent technologies. Familiarity with AI evaluation, observability, tracing, and LLM cost optimization. Experience with cloud-native architecture, infrastructure as code, and application monitoring. ...

with highly relevant sustainable vendor profiles and local circular economies. Infrastructure & Data Pipelines: Build and optimize scalable vector database infrastructures (e.g., Pinecone, Milvus, or pgvector) and real-time streaming architectures alongside backend tech stacks. Technical Leadership & Governance: Pioneer technical guardrails around AI model evaluation, data bias minimization, model quantization ...

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 ...

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 ...

experimental projectsStrong Docker, Kubernetes/OpenShift, CI/CD and pytest knowledgeExperience working with large codebases and improving existing services safelyKnowledge of Azure, RAG, pgvector, Chroma, FAISS, Entra ID, OAuth/OIDC, Redis, Terraform, Prometheus or OpenTelemetry would strengthen your application. Current or recently held SC clearance is required. ...

weight models) with tools, data, and external systems through MCP and custom connectors. Apply RAG techniques where they actuallyhelp:vector databases (Pinecone, Chroma,Weaviate,pgvector), hybrid retrieval withElasticSearchorSolr, and BM25 + similarity search. Work across relational, document, key‐value, and graph stores as the problem demands; use event‐driven patterns ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

governance practices, ideally in a regulated environment. Preferred qualifications: Background in financial services or another regulated enterprise environment. Experience with vector databases (for example pgvector, Pinecone, Weaviate, or Chroma) and agent or orchestration frameworks (for example LangChain, LlamaIndex, or the Model Context Protocol). Experience with MLOps/LLMOps tooling ...

have experience with: Agentic AI and multi-agent systems. LangChain, LangGraph or similar orchestration frameworks. Retrieval-Augmented Generation (RAG). Vector Databases (pgvector, Pinecone, Weaviate, Milvus, etc.). Model Context Protocol (MCP). FastAPI or modern Python backend frameworks. CI/CD and MLOps practices. Building production AI systems ...

/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 ...

Google ADK), or durable workflow engines (e.g., Temporal, Prefect). Memory & Retrieval: Experience with agent memory designs (session, long-term, compaction), vector databases (e.g., pgvector, Qdrant), or hybrid search. Coding Agent Harnesses: Experience configuring coding agents for teams: skills, subagents, hooks, and sandboxing. Nice to Have Gateways & Routing: Experience running ...

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 as Code (Terraform, CloudFormation) Experience ...

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 as Code (Terraform, CloudFormation) Experience with ...

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 plusCloud-Native ...