601 to 625 of 878 Retrieval-Augmented Generation Jobs in the UK

Language Models (LLMs), AI-assisted development tools, and modern AI frameworks. Has understanding of AI system architecture, prompt engineering, vector databases, RAG (Retrieval-Augmented Generation), and AI service integration and has experience evaluating Has knowledge of database systems and excellent problem-solving skills ...

experience across some or all of the following: Generative AI, Large Language Models (LLMs), AI assistants and AI agents. Retrieval Augmented Generation (RAG), enterprise search and knowledge management solutions. Solution, platform or enterprise architecture. Data architecture, integration, APIs and governance. Security, compliance, risk management ...

experience across some or all of the following: Generative AI, Large Language Models (LLMs), AI assistants and AI agents. Retrieval Augmented Generation (RAG), enterprise search and knowledge management solutions. Solution, platform or enterprise architecture. Data architecture, integration, APIs and governance. Security, compliance, risk management ...

experience across some or all of the following: Generative AI, Large Language Models (LLMs), AI assistants and AI agents. Retrieval Augmented Generation (RAG), enterprise search and knowledge management solutions. Solution, platform or enterprise architecture. Data architecture, integration, APIs and governance. Security, compliance, risk management ...

offerings. Deep understanding of modern LLM agent architectures, including multi-agent systems, tool-augmented reasoning, memory and retrieval, programmatic orchestration, RAG, and long-horizon executionStrong grasp of agentic evaluation design, including how to measure task completion, failure recovery, and long-horizon reliability, and how to diagnose ...

focused on production AI: grounded assistants, agentic workflows, evaluation harnesses, and the governance controls that make them safe to run. Design production AI systems: RAG pipelines, agent workflows, tool integrations. Define evaluation, monitoring, and rollback strategies for AI features. Advise clients on model selection, vendor trade-offs, and build ...

extract patterns from one-off work and turn them into reusable assets for others.**Applied AI and Agentic Systems*** Experience building with LLMs, agents, RAG, tool use, workflow orchestration, or automation systems.* Ability to reason about multi-agent, human-in-the-loop, and enterprise integration patterns.* Comfort debugging agent behavior ...

behavioural AI platform and helping scale it from the ground up. You will build and ship AI-powered products end-to-end, own the RAG layer, implement secure, production-grade systems, and collaborate with the VP of Product Engineering to shape the product roadmap. #J-18808-Ljbffr ...

Capgemini is seeking a GenAI Architect in London to lead architecture and delivery of enterprise-scale AI solutions on AWS, leveraging Bedrock and RAG techniques. You will shape reusable patterns for prompt orchestration, agentic workflows, and observability while working with security, compliance and engineering teams. The role emphasizes governance, model ...

traditional projects. You will work with a multidisciplinary team to deliver production‐ready platforms and apply cutting‐edge techniques. You will gain exposure to RAG, LLMs and cloud-native architectures, with a strong focus on secure, scalable delivery and effective collaboration with stakeholders across the business. #J-18808-Ljbffr ...

learning is essential, with solid NLP and financial knowledge and hands‐on implementation experience. The role focuses on advanced techniques such as semantic search, RAG, NER, prompt engineering, and personalization for content #J-18808-Ljbffr ...

Stack) to design, build, and operate production-grade AI systems based on foundation models. You will own end-to-end LLM-powered applications, including RAG workflows, with a focus on reliability, scalability, and safety. This on-site role sits within the Data & AI Team in Cambridge and reports ...

Experience within Azure environments Strong stakeholder engagement in large enterprise environments Experience in regulated industries is highly desirable Exposure to Neo4j, Microsoft Graph, GraphRAG, RAG or vector databases would be beneficial. ...

across frontend and backend development, with a solid understanding of system design and API architecture. Experience building AI-powered applications, including working with LLMs, RAG systems, and related technologies. Demonstrated ability to take ownership of features from concept through production, making pragmatic engineering decisions while thriving in fast-paced, evolving ...

years of experience managing large tech, cloud, or consulting projects. Mandatory Tech Skills: Real, hands-on experience with AWS AI services-specifically Amazon Bedrock (RAG, prompt engineering) and AgentCore . Service Management: A strong background in SIAM and ITSM frameworks. Leadership: proven ability to comfortably talk tech with developers ...

years of experience managing large tech, cloud, or consulting projects. Mandatory Tech Skills: Real, hands-on experience with AWS AI services-specifically Amazon Bedrock (RAG, prompt engineering) and AgentCore . Service Management: A strong background in SIAM and ITSM frameworks. Leadership: proven ability to comfortably talk tech with developers ...

product management experience, translating customer needs into actionable roadmaps Experience leading or coordinating technical teams Comfortable discussing modern AI/software technologies including LLMs, RAG and data pipelines Strong commercial, scope, budget and delivery management skills Comfortable operating autonomously in a fast-moving environment Excellent communication skills across technical, scientific ...

Assurance You'll also have a good understanding of how AI systems actually introduce security risk — whether that's through LLM applications, APIs, RAG, agents, tool use, data access or autonomous workflows. Experience with NIST AI RMF, OWASP LLM/Agentic AI guidance, MITRE ATLAS, ISO 27001, NIST ...

degree or equivalent practical experience. 7 years of experience project managing and delivering technical solutions. Experience designing end-to-end AI systems (e.g., RAG, vector databases, and API integrations) and defining AI product/workflow specifications. Experience leading cross-functional teams, driving technical deployments, and managing stakeholders. Preferred qualifications: Experience ...

data domain experience or experience as a trading-platform user. Open-source contributions to AI tooling (LangChain, LlamaIndex, vLLM, DSPy, or similar). Production RAG and vector-database experience; experience with code-generation, transpilation, or developer-experience tooling. Logistics Location: Europe (EU/UK) — fully remote; must overlap ...

advisor to client CxOs. Key Responsibilities Architecture and Solution Design: Architect enterprise AI solutions using frontier models (Claude, GPT, Gemini family) across agentic automation, RAG, copilots, and multi-modal applications. Pre-Sales and Discovery: Lead technical solutioning during pre-sales and discovery, translating client business challenges into scalable AI architectures … specifically on applied AI/ML or Generative AI. Hands-on GenAI Depth: Proven experience architecting solutions with frontier modelsincluding prompt engineering, fine-tuning, RAG, and agentic/multi-agent system design. LLMOps/MLOps Grounding: Expertise in evaluation frameworks, observability, cost and latency optimization, guardrails, and safe deployment ...

advisor to client CxOs. Key Responsibilities Architecture and Solution Design: Architect enterprise AI solutions using frontier models (Claude, GPT, Gemini family) across agentic automation, RAG, copilots, and multi-modal applications. Pre-Sales and Discovery: Lead technical solutioning during pre-sales and discovery, translating client business challenges into scalable AI architectures … specifically on applied AI/ML or Generative AI. Hands-on GenAI Depth: Proven experience architecting solutions with frontier modelsincluding prompt engineering, fine-tuning, RAG, and agentic/multi-agent system design. LLMOps/MLOps Grounding: Expertise in evaluation frameworks, observability, cost and latency optimization, guardrails, and safe deployment ...

advisor to client CxOs. Key Responsibilities Architecture and Solution Design: Architect enterprise AI solutions using frontier models (Claude, GPT, Gemini family) across agentic automation, RAG, copilots, and multi-modal applications. Pre-Sales and Discovery: Lead technical solutioning during pre-sales and discovery, translating client business challenges into scalable AI architectures … specifically on applied AI/ML or Generative AI. Hands-on GenAI Depth: Proven experience architecting solutions with frontier modelsincluding prompt engineering, fine-tuning, RAG, and agentic/multi-agent system design. LLMOps/MLOps Grounding: Expertise in evaluation frameworks, observability, cost and latency optimization, guardrails, and safe deployment ...

advisor to client CxOs. Key Responsibilities Architecture and Solution Design: Architect enterprise AI solutions using frontier models (Claude, GPT, Gemini family) across agentic automation, RAG, copilots, and multi-modal applications. Pre-Sales and Discovery: Lead technical solutioning during pre-sales and discovery, translating client business challenges into scalable AI architectures … specifically on applied AI/ML or Generative AI. Hands-on GenAI Depth: Proven experience architecting solutions with frontier modelsincluding prompt engineering, fine-tuning, RAG, and agentic/multi-agent system design. LLMOps/MLOps Grounding: Expertise in evaluation frameworks, observability, cost and latency optimization, guardrails, and safe deployment ...

advisor to client CxOs. Key Responsibilities Architecture and Solution Design: Architect enterprise AI solutions using frontier models (Claude, GPT, Gemini family) across agentic automation, RAG, copilots, and multi-modal applications. Pre-Sales and Discovery: Lead technical solutioning during pre-sales and discovery, translating client business challenges into scalable AI architectures … specifically on applied AI/ML or Generative AI. Hands-on GenAI Depth: Proven experience architecting solutions with frontier modelsincluding prompt engineering, fine-tuning, RAG, and agentic/multi-agent system design. LLMOps/MLOps Grounding: Expertise in evaluation frameworks, observability, cost and latency optimization, guardrails, and safe deployment ...