51 to 75 of 100 Semantic Search Jobs in the UK

speech ElevenLabs AWS Bedrock Amazon SageMaker Google Cloud Platform (GCP) Vertex AI Python FastAPI/APIs LangChain/LangGraph Vector databases Embeddings and semantic search Hugging Face/open-source AI models Prompt engineering Model evaluation and optimisation MLOps/LLMOps Docker/Kubernetes CI/CD Cloud ...

Claude, Gemini, or Azure AI Experience building Agentic AI workflows, orchestration frameworks, AI copilots, or autonomous process automation solutions Knowledge of AI-driven APIs, semantic search, RAG architectures, and vector database integrations Azure certifications such as AZ-900, AZ-204, or AI-900 would be advantageous Key Responsibilities ...

Forum SID, Open API, or Autonomous Networks training.**Nice-to-Have Qualifications*** Experience with telecom digital twin platforms.* Experience with vector databases, embeddings, semantic search, or RAG.* Experience with streaming data platforms such as Kafka, Pub/Sub, Flink, or Spark Streaming.* Experience supporting closed-loop automation, predictive ...

multi-agent systems, including role definition, tool integration, planning, memory, and workflow orchestration using modern agent frameworks. Implement Retrieval-Augmented Generation (RAG) pipelines and semantic search with vector databases, including indexing, retrieval policies, and evaluation. Build and integrate agent tools and APIs to connect agents with external services ...

infrastructure and datacenter teams through APIs, CLI, dashboards, and Slack. Core Agent Platform — Build the platform that powers these agents, including knowledge graphs, search and retrieval, orchestration, evaluation, and the tooling that enables agents to reason, act, and continuously improve. We’re working on something that hasn’t really … production. Depth in at least one of the following: AI agent systems, orchestration, tool use, evaluation, or grounding Knowledge graphs or graph data modeling Search, retrieval, ranking, RAG, or semantic search systems Strong backend engineering experience, including API design, service boundaries, data modeling, and integrations across complex ...

role: - Design AI and GenAI architecture strategies and roadmaps - Build scalable AI/ML and Agentic AI platforms - Work across LLMs, RAG, embeddings and semantic search - Support AI deployment, governance and integration patterns - Collaborate with engineering, data, DevOps and business teams - Advise clients on AI platform capability ...

requirements into robust, scalable data solutions. Develop conceptual, logical, and physical data models. Design and implement modern AI-ready architectures, including RAG, vector databases, semantic search, and LLM integrations. Build and optimise data pipelines supporting both batch and real-time processing. Lead data integration, transformation, and migration initiatives. ...

GenAI architecture strategy and roadmap. Build scalable AI/ML and Agentic AI platforms spanning LLMs, retrieval-augmented generation (RAG), embeddings and semantic search. Lead on deployment, governance and integration patterns, advise clients on platform capability and implementation strategy, and partner with engineering, data, DevOps and business teams ...

that scales seamlessly. Standardization of Tooling: Define and enforce the organization's official AI stack, from vector database selection and vector embeddings strategies to semantic caching mechanisms. Vendor & Open-Source Strategy: Evaluate and manage partnerships with AI model providers and lead the technical assessment of cutting-edge open-source … successfully built and scaled AI-powered applications in 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 ...

Databricks or similar technologies·Experience architecting scalable AI and ML solutions across serverless, containerised or GPU enabled environments·Experience with LLMs, prompt engineering, embeddings, semantic search and RAG patterns·Exposure to vector databases and agent frameworks such as LangChain, LangGraph or similar technologies·Understanding of MLOps, LLMOps ...

GenAI architecture strategy and roadmap. Build scalable AI/ML and Agentic AI platforms spanning LLMs, retrieval-augmented generation (RAG), embeddings and semantic search. Lead on deployment, governance and integration patterns, advise clients on platform capability and implementation strategy, and partner with engineering, data, DevOps and business teams ...

ambiguous environments and owning projects from concept to deployment. Nice to Have Experience with Retrieval-Augmented Generation (RAG). Knowledge of vector databases and semantic search. Experience with Python alongside TypeScript. Familiarity with AI orchestration frameworks such as LangChain, LangGraph, or similar. Experience with CI/CD pipelines, Infrastructure ...

Model Context Protocol) or similar frameworks. Experience with LLM providers (OpenAI, Anthropic) for inference and evaluation. Working knowledge of vector databases, embedding models, and semantic search. Experience with coding assistants (GitHub Copilot, Cursor) in a developer productivity context. Multi‐site or international delivery experience. What We’re Looking ...

Kharon is seeking a full-time Data Scientist for Retrieval & Agentic Systems based in London. You will own Corestream and evolve semantic search, leveraging BM25, vector search, RAG, and RDF-like pipelines. You will integrate risk outputs into search and drive narrative generation, collaborating with Product ...

LLMs, prompt engineering, agent behavior, reasoning patterns, context management, memory, tool calling, and workflow orchestration. Strong expertise in NLU, intent and entity modeling, semantic understanding, dialogue management, clarification strategies, and conversational design. Experience translating business rules and operational workflows into AI decision logic and user experiences. Experience designing guardrails … failure handling, and responsible AI practices. Experience defining AI evaluation frameworks and using interaction data, testing, and analytics to improve performance. Knowledge of RAG, semantic search, enterprise knowledge systems, grounding, observability, and regression testing. Working knowledge of APIs, cloud services, software architecture, integration patterns, and modern engineering practices. ...

governed, scalable, and AI-consumable Develop, maintain, and prioritize the product backlog across functional and non-functional requirements — covering the Integration Fabric, Knowledge Graph, Search, Permissions, Governance, Observability, APIs, and MCP layers Author clear, well-groomed user stories with defined acceptance criteria; lead sprint planning, estimation, retrospectives, and scrum … solid understanding of compliance, data governance, and access control requirements Hands‐on familiarity with knowledge management technologies: SharePoint Online/M365, graph databases, semantic search, vector stores, or enterprise content platforms Experience with enterprise search and knowledge discovery platforms, including evaluation, implementation, or scaled deployment of intelligent ...

automation from their data. Key Responsibilities: Design and develop Agentic AI applications and workflows Build and optimise Knowledge Graphs using Neo4j Develop GraphRAG and semantic search solutions Integrate LLMs with enterprise data sources Work closely with engineering and data teams to deliver production-ready AI systems Required Skills ...

asset management. Job Responsibilities Design and implement agentic AI workflows that automate and streamline complex business processes. Design and apply advanced techniques such as semantic search, retrieval‐augmented generation (RAG), named entity recognition (NER), prompt engineering, and personalization for content extraction, search, question answering, reasoning, and recommendation. ...

fast‐growing startups or enterprise software companies Knowledge of financial planning, analytics, or business intelligence domains Experience with RAG systems, vector databases, and semantic search Familiarity with model fine‐tuning, evaluation, and continuous improvement workflows Background in distributed systems, microservices, or cloud‐native architectures Our Commitment to Diversity ...

each problem, using approaches such as classification, regression, clustering, ranking, feature engineering, deep learning, embeddings, LLMs, retrieval, and generative AI. Develop capabilities for semantic search, information retrieval, entity extraction, content classification, recommendation, ranking, summarization, question answering, and evidence-grounded generation. Build, evaluate, fine-tune, prompt, and integrate models ...

fast-growing startups or enterprise software companies Knowledge of financial planning, analytics, or business intelligence domains Experience with RAG systems, vector databases, and semantic search Familiarity with model fine-tuning, evaluation, and continuous improvement workflows Background in distributed systems, microservices, or cloud-native architectures Our Commitment to Diversity ...

managing containerized workloads and automated CI/CD pipelines. Advanced RAG: Experience building production-ready Retrieval-Augmented Generation systems, including vector database management and semantic search optimization. Preferred Qualifications Experience in the insurance or financial services sector. Deep knowledge of GPU architecture , CUDA, and hardware-level performance optimization. ...

security and identity management. Excellent stakeholder engagement and communication skills. Desirable ExperienceFinancial services or other highly regulated sectors. Azure OpenAI and enterprise GenAI platforms. Semantic search, vector databases and knowledge architecture. Microsoft Graph, SharePoint and collaboration platform integrations. Knowledge of AI governance, GDPR, EU AI Act and operational ...

robust evaluation frameworks: build test sets, define metrics, evaluate non-deterministic systems, handle class imbalance, and automate checkpoint comparisons. Improve and extend semantic search and retrieval, evolving from embedding-based approaches toward more advanced methods. Write production-quality code and collaborate closely with Engineering on productionisation, model serving ...

accessible APIs Slack, Microsoft Graph, SharePoint, OneDrive, Outlook, Teams, Google Workspace, Jira, Snowflake, Figma or similar workplace and business-system APIs Permission-aware retrieval, semantic search, embeddings, vector databases, knowledge graphs, document indexing or source-attributed answer generation Agent SDKs, workflow frameworks or application libraries such ...