25 of 25 pgvector Jobs in the UK

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 ...

LangGraph, LlamaIndex, and Hugging Face, including agentic and multi‐step workflows. Proven experience designing and implementing Retrieval‐Augmented Generation (RAG) systems, including vector databases (pgvector, Pinecone, Weaviate, FAISS, etc.) and advanced retrieval strategies (hybrid search, re‐ranking, metadata filtering). Strong understanding of prompt engineering, workflow design ...

engineering, RAG, embeddings and vector search • Proven experience building agentic AI with LangGraph or similar (LangChain, Semantic Kernel, AutoGen, CrewAI) • Experience with vector databases (pgvector, Azure AI Search, Pinecone, Weaviate, Chroma, FAISS, Milvus or OpenSearch) • Cloud (Azure/AWS/GCP), Docker and Kubernetes • Solid grasp of API integration, tool ...

with observability tools such as OpenTelemetry, LangSmith, Arize/Phoenix, Helicone, Portkey, or similar platforms. Experience with vector databases and search systems such as pgvector, Qdrant, Weaviate, Pinecone, OpenSearch, Elasticsearch, or Vespa. Experience with cloud platforms such as AWS, Azure, GCP, Vercel, Cloudflare, or Kubernetes-based environments. Experience with identity ...

Experience with continuous integration and deployment tools such as GitLab, GitHub, or Jenkins.Database ManagementVector 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 ControlProficient in Git and version control platforms ...

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 such ...

models) with tools, data, and external systems through MCP and custom connectors. Apply RAG techniques where they actually help: vector databases (Pinecone, Chroma, Weaviate, pgvector), hybrid retrieval with Elasticsearch or Solr, and BM25 + similarity search. Work across relational, document, key-value, and graph stores as the problem demands ...

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 ...

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 ...

technologies is highly desirable: Frameworks & Infrastructure: Apache Spark Apache Airflow Kafka Elasticsearch/OpenSearch Databases: PostgreSQL MongoDB Vector databases such as Qdrant, Milvus, or pgvector Python Ecosystem: Pandas Polars Engineering Skills: Experience building highly scalable backend systems. Strong understanding of data modelling and storage architecture. Deep knowledge of data processing ...

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 ...

enterprise SaaS or complex data platforms. AI & Engineering Mastery: Deep technical expertise in Python or Go, semantic search, vector databases (e.g., Pinecone, Milvus, pgvector), orchestration frameworks (LangChain, LlamaIndex), and fine-tuning or prompt engineering of state-of-the-art Large Language Models (LLMs). Extreme Ownership: High-agency mindset. ...

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 ...

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 ...

/functions callable by AI agents (tool schemas, function calling, structured outputs). Experience with retrieval-augmented generation (RAG): vector databases (eg, 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 ...

Strong understanding of modern software development principles, clean code practices, data structures, algorithms, and distributed systems. Proficiency with Relational (preferably, PostgreSQL) and Vector (preferably, pgvector) databases. Preferred Qualifications (Bonus Points): Proficiency in additional programming languages such as Java, JavaScript/TypeScript, or Golang. Experience with specific frameworks like Spring ...

loops: planner/executor/verifier patterns, tool‐use schemas, retry + escalation logic. Build retrieval pipelines: chunking strategy, vector DB choice (Pinecone/pgvector/Weaviate), reranking, freshness handling. Stay current on Anthropic + OpenAI release notes; adjust prompts + schemas when APIs evolve. We treat the foundation‐model ...

Expertise: 2+ years of hands‐on experience building and productionising LLM applications, with deep technical knowledge of vector databases (e.g., Qdrant, Weaviate, Pinecone, pgvector) and orchestration layers (e.g., LangGraph, LlamaIndex). Comfortable working with heterogeneous documents like pdfs. Experience working with re‐ranking models. Production-Grade Asynchronous Python: Strong software ...

graph models for complex reaction networks, define the semantic ontologies that let AI reason across different chemical data types, and design vector search (e.g. pgvector, Pinecone) for similarity lookups across large molecular sets. Design the telemetry pipeline. Specify streaming ingestion for high-frequency robot and sensor data, with zero loss ...

Senior Machine Learning Engineer ££75,000 GBP Hybrid WORKING Location: Central London, Greater London - United Kingdom Type: Permanent Senior Machine Learning Engineer Location: London (Hybrid) Salary: £75,000 + Bonus + Excellent Benefits Are you ...

safely. Retrieval‐Augmented Generation (RAG) & Knowledge Systems : Proven experience designing RAG and knowledge‐grounded systems, including chunking strategies, embeddings, vector databases (Pinecone, Weaviate, Chroma, pgvector, FAISS), hybrid search, reranking, and evaluation of retrieval quality. Familiarity with advanced patterns such as GraphRAG and agentic RAG to reduce hallucination and improve factual … patterns Cloud AI platforms & model hosting: Amazon Bedrock, Azure OpenAI/AI Foundry, Google Vertex AI, Hugging Face Vector databases & retrieval: Pinecone, Weaviate, Chroma, pgvector, FAISS; embeddings, semantic and hybrid search, reranking MLOps/LLMOps & deployment: Docker, Kubernetes, FastAPI, CI/CD; observability, tracing, evaluation tooling (LangSmith, LangFuse); guardrails, prompt ...

mindset with a strong sense of ownership Excellent communication and collaboration skills Nice-to-have MongoDB and OpenSearch Vector databases (Qdrant, Weaviate, Milvus, Pinecone, pgvector) OIDC or identity infrastructure Infisical, PostHog, Oh Dear, or similar tooling AI/LLM platform experience GDPR-conscious cloud environments Enterprise security and compliance experience ...

systems, not just prototypes Demonstrable experience of building and deploying complex AI applications using LLMs and ideally, agentic workflows A familiarity with vector databases (pgvector, ChromaDB, Pinecone or similar) is a plus Benefits include: Flexibility - the team works fully remotely, albeit with frequent meetups to share ideas Stock options Excellent ...

systems, not just prototypes Demonstrable experience of building and deploying complex AI applications using LLMs and ideally, agentic workflows A familiarity with vector databases (pgvector, ChromaDB, Pinecone or similar) is a plus Benefits include: Flexibility - the team works fully remotely, albeit with frequent meetups to share ideas Stock options Excellent ...

loops. Author custom skills and slash commands for Claude Code to codify team‐specific workflows. Implement RAG pipelines and integrate vector stores (e.g., Qdrant, pgvector, Pinecone) to ground agent outputs in trusted data. Instrument agents for evaluation and observability so their outputs can be verified, measured, and audited. Apply … Model Context Protocol) for connecting agents to internal tools and data sources. Working knowledge of RAG patterns and vector store integration (e.g., Qdrant, pgvector, Pinecone). Awareness of AI‐specific risk areas relevant to a regulated environment (OWASP LLM Top 10, hallucination/determinism concerns, and auditability of agent decisions ...