3 of 3 Permanent Azure Cognitive Search Jobs in the City of London

AI Solutions Architect

Hiring Organisation
Tadaweb
Location
City of London, London, United Kingdom
vector search. Vector Search Strategy : Define approach for semantic retrieval using pgvector, AlloyDB AI, or Azure Cognitive Search with embeddings. Cost & Performance : Establish strategies for latency optimization and cost control across clouds. AI Enablement & Delivery RAG System Design : Implement … Azure AI services . Practical knowledge of vector search (pgvector, AlloyDB AI, Azure Cognitive Search) and RAG orchestration. Strong Python or TypeScript for prototyping and integration. Familiarity with multi-cloud security and IAM patterns. ...

Senior Knowledge & Information Management Consultant

Hiring Organisation
DataCareers
Location
City Of London, England, United Kingdom
realised. Advise senior stakeholders on KIM strategy, operating models, policies, and controls . Define target states for information architecture, content lifecycle, records management, search, and knowledge capture & reuse . Translate strategy into executable roadmaps with clear benefits and sequencing. Design and implement governance and change/adoption … structures. Familiarity with tools such as Microsoft 365 (SharePoint, Teams, Purview), OpenText, Content Manager (TRIM), Documentum, Confluence, Elastic, or Azure Cognitive Search . Change and adoption experience, including measurement of behavioural impact. Security-aware delivery in regulated or classified environments. Active ...

Senior AI Engineer

Hiring Organisation
Xcede
Location
City of London, London, United Kingdom
text files, spreadsheets, structured JSON, and audio sources Design intelligent retrieval systems that combine structured chunking, advanced indexing, re-ranking methods, and hybrid search approaches Develop machine learning and LLM-based applications for tasks like information extraction, document classification, summarisation, and semantic querying Construct and maintain multi … factuality, and relevance Collaborate closely with product, engineering, and data teams to embed AI capabilities into user-facing platforms Deploy solutions in an Azure-based cloud environment, using container orchestration, automation pipelines, secure key management, and observability tooling Enforce data security and responsible AI practices, including anonymisation ...