10 of 10 pgvector Jobs in the UK excluding London

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 ...

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 ...

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 ...

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 ...

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 ...

DOCX and HTML, including layout-aware parsing (headings, tables, multi-column pages) • RAG retrieval pipelines: Chunking strategy, embedding models, vector search (Postgres with pgvector or similar) and metadata design • Postgres: Schema design, indexing (including vector indexes) and performance at scale • Retrieval evaluation: Building labelled ground-truth datasets and measuring retrieval ...

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 technical workshops and explaining ...