351 to 375 of 954 Retrieval-Augmented Generation Jobs in England

infrastructure required to run AI workloads reliably, moving client architectures from static data lakes to dynamic Vector Databases and Retrieval‐Augmented Generation (RAG) architectures. Agentic Development: Build production‐grade Agentic Workflows and custom AI agents, utilising advanced toolsets to bridge the widening market implementation … maintaining data orchestration toolsets (e.g., dbt, Apache Airflow), ETL/ELT methodologies, real‐time streaming (e.g., AWS Kinesis, Apache Kafka), Vector databases, and RAG architectures. Observability & FinOps: Experience implementing modern observability tooling (OpenTelemetry) alongside automated cost‐control systems (such as Karpenter, Infracost, OpenCost, or Cloud Custodian). Domain & Sector Experience ...

infrastructure required to run AI workloads reliably, moving client architectures from static data lakes to dynamic Vector Databases and Retrieval‐Augmented Generation (RAG) architectures. Agentic Development: Build production‐grade Agentic Workflows and custom AI agents, utilising advanced toolsets to bridge the widening market implementation … maintaining data orchestration toolsets (e.g., dbt, Apache Airflow), ETL/ELT methodologies, real‐time streaming (e.g., AWS Kinesis, Apache Kafka), Vector databases, and RAG architectures. Observability & FinOps: Experience implementing modern observability tooling (OpenTelemetry) alongside automated cost‐control systems (such as Karpenter, Infracost, OpenCost, or Cloud Custodian). Domain & Sector Experience ...

earlier in the lifecycle. You will also support the adoption of AI/GenAI capabilities in practical QE use cases such as test generation, defect analysis, and quality reporting.What you'll be doing:Design, build, test, and maintain quality engineering solutions across the SDLCContribute to the development … enabled engineering solutions, ideally in testing, automation, or developer productivity use cases.This may include experience with:AI application patternsRetrieval-Augmentation Generation (RAG)prompt engineeringtool callingagentic workflowsevaluation of LLM-based outputsFrameworks and orchestrationLangChainLangGraphCrewAIModels and platformsOpenAI and/or Azure OpenAIVector search and retrievalWeaviate or equivalent vector database technologyData ...

Python and experience with AI/ML libraries. Familiarity with cloud infrastructure (AWS preferred) for deploying AI systems. Understanding of RAG (Retrieval-Augmented Generation), vector databases, and memory systems. Experience with RPA or automation tooling is desirable. Knowledge of responsible AI principles ...

practical experience. Machine Learning: Expertise in time‐series forecasting, clustering, and correlation algorithms. Generative AI: Experience with LLM prompting, Retrieval‐Augmented Generation (RAG), and LangChain. Cloud Infrastructure: Deep understanding of AWS, Azure, or GCP infrastructure components Additional Preferred Qualifications: Experience with enterprise observability ...

science capability. And any experience of this would be really useful. Building agentic AI solutions, LLM‐powered applications and retrieval‐augmented generation (RAG) architectures. Experience with Vertex AI Agent Builder, Agentspace, LangGraph or multi‐agent frameworks. Knowledge of responsible AI, model governance and risk ...

technical audiences. Experience gathering and synthesizing requirements across multiple stakeholder groups and influencing product or platform roadmaps. Familiarity with LLM ecosystems (e.g., prompting, RAG, agents, MCP, fine‐tuning, evaluation) and major AI platforms/APIs. Experience in financial services, asset management, or portfolio analytics is a strong plus. Good ...

preferred), Docker/Kubernetes, CI/CD, and monitoring Strong debugging, collaboration, and continuous-learning mindset Nice to Have: Experience with vector databases and RAG (e.g., OpenSearch, ElasticSearch) Ready to build what's next? Oscar Associates (UK) Limited is acting as an Employment Agency in relation to this vacancy. ...

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 and model lifecycle management principles·Experience ...

moving environment where technologies and best practices are continually evolving. Desirable Experience with Azure OpenAI. Experience building AI agents or agentic workflows. Knowledge of RAG, embeddings and vector databases/search. Experience with Azure AI Search. Familiarity with prompt engineering and evaluation of LLM applications. Experience with Azure DevOps ...

Desirable Experience with other AI platforms (Bedrock) IaC (Terraform/Bicep) for building AI platforms Experience building AI agents or agentic workflows. Knowledge of RAG, embeddings and vector databases/search. Experience with Azure AI Search. Familiarity with prompt engineering and evaluation of LLM applications. Experience with Azure DevOps ...

backend API services, model integration, model monitoring, evaluations and deployments Integrate and optimise LLMs for specific use cases in business planning, including prompt engineering, RAG implementation Build conversational interfaces and agentic workflows that make complex planning tasks accessible through natural language Implement evaluation frameworks to measure and improve GenAI feature ...

influencing and communicating with stakeholders across technical and non-technical teamsIdeally, exposure to cloud infrastructure, NLP or large language models (such as fine-tuning, RAG or agents), graph technologies, or experience in the transport sector or with geographic information systems (GIS)More information:Enjoy fantastic perks like private healthcare & dental ...

communicating with stakeholders across technical and non-technical teams Ideally, exposure to cloud infrastructure, NLP or large language models (such as fine-tuning, RAG or agents), graph technologies, or experience in the transport sector or with geographic information systems (GIS) More information: Enjoy fantastic perks like private healthcare & dental insurance ...

Intelligence or Generative AI.Demonstrated ability to architect end-to-end Data & AI solutions, with specific expertise in modern Generative AI concepts (e.g., fine-tuning, RAG, MLOps for LLMs), using either open source and/or ISV tools such as Dataiku, Domino, DataRobot etc.Strong proficiency in a core programming language (e.g. ...

software engineering experience with strong backend/API expertise using Python (FastAPI or Flask).1+ years of hands-on experience with LLMs: building RAG solutions, agentic workflows, integrating LLMs (e.g., OpenAI, Gemini, Anthropic, etc.) into products, building and integrating Model Context Protocol (MCP) servers, and authoring Claude Skills to extend ...

production LLM workflows, including prompt/skill design, evaluation, cost control, provider routing, agentic/human‐in‐the‐loop orchestration, embeddings, vector search and RAG Implementation of foundational ML algorithms, classic NLP techniques and LLMs Strong SQL for analytical and production use, ideally PostgreSQL, including complex joins, CTEs and aggregation ...

backend API services, model integration, model monitoring, evaluations and deployments Integrate and optimise LLMs for specific use cases in business planning, including prompt engineering, RAG implementation Build conversational interfaces and agentic workflows that make complex planning tasks accessible through natural language Implement evaluation frameworks to measure and improve GenAI feature ...

product estate. Disciplined use of AI tools across the delivery process with the ability to validate output, supported by optional experience in production LLMs, RAG, and AI agents. Proven background in customer-facing technical delivery, spanning pre-sales technical discovery, hands-on implementation, and escalation management. Excellent communication skills ...

topics credibly in customer conversations, while governance strategy and roadmap ownership sit with a dedicated specialist role. Practical understanding of how AI workloads — LLMs, RAG, agentic AI — consume enterprise data. The emphasis is on engineering trusted, scalable data foundations, not building AI models. Experience integrating and using AI coding assistants ...

support controls and audits. Architecture across cloud + AI: Strong software architecture background spanning cloud‐native, integration, and GenAI/agentic patterns (e.g., RAG, orchestration, tool use), with a pragmatic approach to delivery. GenAI across the SDLC: Practical use of GenAI in delivery, including requirements elaboration, ADRs (Architectural Decision Record ...

Matillion product estate.Disciplined use of AI tools across the delivery process with the ability to validate output, supported by optional experience in production LLMs, RAG, and AI agents.Proven background in customer-facing technical delivery, spanning pre-sales technical discovery, hands-on implementation, and escalation management.Excellent communication skills to connect with ...

learning or Generative AI to be a genuine peer to your architects and engineers. You should be able to explain, without notes, how a RAG architecture fails in production and what you would do about it. • Team leadership. Experience leading and coaching consultants, engineers or architects within your programme ...

architecture for unstructured document ingestion, reasoning, and output generation Design LLM-centric and hybrid AI architectures combining: OCR RAG systems Agentic workflows Design and govern prompt strategies and prompt frameworks for: Loss run and insurance document extraction & normalization Claims summarization, triage, and fraud signal generation Underwriting … platforms Experience integrating AI solutions into enterprise systems .NET (Backend) and React (Frontend) Developer Prompt Engineering & LLM Design Retrieval Augmented Generation (RAG) Architectures Skills and Personal attributes we would like to have: OCR systems for document ingestion and classification AI Governance & Token Economics ...

prompt engineering combined with traditional software/automation engineering. Hands-on expertise utilizing GitHub Copilot, Microsoft Copilot, and Claude Code for code generation, review, and refactoring. Deep proficiency in PowerShell scripting, enterprise automation, and system administration. Strong database background, specifically with SQL Server. Programming proficiency in at least … with Azure AI, OpenAI APIs, or Anthropic APIs. Solid understanding of CI/CD, DevOps, and enterprise automation platforms. Familiarity with RAG (Retrieval-Augmented Generation) architectures, vector databases, and knowledge systems. Previous experience deploying AI solutions within large-scale or regulated enterprise environments. ...