226 to 250 of 399 Retrieval-Augmented Generation Jobs in the UK

Identifying opportunities to adopt AI into new or existing digital servicesLeading AI solution design using modern patterns such as retrieval‐augmented generation (RAG), multi-agent orchestration, vector search, prompt chaining, and model fine‐tuning.Demonstrating hands-on ability to assess technical feasibility of AI concepts … services, DevOps and waterfall environments before and know the challenges to bring the best of old and new worldAbility to develop our next generation of digital architects through formal line management and informal mentoring, coaching and learning developmentWHAT YOU'LL LOVE ABOUT WORKING HEREOur Digital Architects ...

opportunities to adopt AI into new or existing digital services* Leading AI solution design using modern patterns such as retrieval‐augmented generation (RAG), multi-agent orchestration, vector search, prompt chaining, and model fine‐tuning.* Demonstrating hands-on ability to assess technical feasibility … DevOps and waterfall environments before and know the challenges to bring the best of old and new world* Ability to develop our next generation of digital architects through formal line management and informal mentoring, coaching and learning development## **WHAT YOU'LL LOVE ABOUT WORKING HERE**Our Digital Architects ...

egress controls). Strong understanding of AI/LLM capabilities and risks across the lifecycle (model onboarding/ingestion, retrieval/RAG patterns, model serving) and associated control points (traceability, access, data handling), including assessing control design and operational effectiveness in fast‐changing environments. Experience with agentic ...

Portfolio Credit Control is seeking a Senior AI Engineer to design, build and scale Agentic AI, Generative AI and RAG solutions powering customer-facing products worldwide. You’ll work with Product, Platform and Engineering to develop production-grade AI systems, autonomous agents and LLM-powered applications. You’ll design ...

Anthropic APIs. The role requires 3-5 years of experience, strong Python/TypeScript skills, and hands-on experience with LLMs, vector databases, and RAG pipelines. #J-18808-Ljbffr ...

multi-agent orchestration (beyond simple chatbots) Hands-on experience with LLM guardrails , cost optimization , and model evaluation frameworks Deep understanding and implementation experience in: RAG architectures Vector stores Embeddings Prompt and response evaluation Strong engineering hygiene with experience in:Automated testingCI/CD pipelinesObservability & monitoringCorrelation IDs and tracingContainerization with Docker ...

scale backend architecture Event-driven systems Developer platforms Production AI infrastructure Experience with technologies such as OpenAI, Anthropic, LangGraph, LangChain, Kubernetes, Kafka, Vector Databases, RAG, MCP, Temporal or similar would be highly advantageous. Ideal backgrounds Current or previous: Chief Technology Officer Founding CTO Technical Co-Founder VP Engineering Head ...

business environment Deep expertise in Python and modern AI/ML frameworks and SDKs Strong experience building and deploying production‐grade AI solutions, including RAG pipelines and LLM‐based applications Hands‐on experience with AI deployment, operationalisation, monitoring, and scaling Strong understanding of enterprise infrastructure concepts including VNets, Entra ...

Experience building or deploying AI/LLM systems in production. Founder or founding engineer experience. Familiarity with AI agent tools: eval frameworks, agent tooling, RAG pipelines, and prompt engineering. Prior experience with React, TypeScript, and/or Go. Experience interfacing with customers or leading technical projects with external stakeholders. What ...

bring a strong STEM/computing background. Knowledge and understanding of UK Defence. Experience in one or more of the following technical disciplines: LLMs, RAG,Agentic AI(e.g. LangGraph). Computer Vision. AI for audio and speech. What we offer We offer a combination of mentoring and internal and external ...

know what it means to balance craft, ownership, and speed Familiarity with tools that power today's AI agents: eval frameworks, agent tooling, RAG pipelines, and prompt engineering Prior experience with React, TypeScript, and/or Go Previous roles where you interfaced with customers or led technical projects with external ...

modern data stacks, and can reason about system design. Practical experience building applications on LLMs (OpenAI, Anthropic, open-source), including prompt engineering and RAG architectures. Experience training, deploying or productionising ML models, and measuring whether they actually work. Ability to translate a vague business problem into a technical solution ...

systems, core banking platforms and the integration challenges of deploying AI within regulated market systems.* Strong command of modern AI capabilities: LLMs, agentic frameworks, RAG, ML inference, and MLOps, sufficient to lead technical teams and challenge engineering decisions.* Demonstrated ability to drive AI adoption at scale, navigating organisational complexity, change ...

inform modelling and business decisions. Build, tune, andoptimisemachine learning, deep learning, and generative AI models,leveragingboth established andcutting-edgetechniques. Designand buildLLM-powered systems— RAG pipelines, prompt and context engineering, fine-tuning, structured outputs, function calling, context-window management,and secure model integration;selectingappropriately between standard and reasoning (test-time-compute … Kubernetes), event-driven or microservices architectures, and distributed data processing at scale. Experience with embedding pipelines, vector search, and semantic retrieval for RAG systems. Knowledge of LLM evaluation techniques including structured evals frameworks, hallucination mitigation, benchmarking, and human-in-the-loop evaluation. Understanding of AI safety, responsible ...

have delivered AI solutions within it. Typical projects include: Building AI agents and autonomous workflows Developing LLM-powered applications and copilots Designing enterprise RAG and knowledge retrieval platforms Production deployment of Generative AI solutions AI integration into enterprise products and business platforms Scaling AI systems across cloud environments … ideally have experience with: Python OpenAI, Anthropic, Gemini, Llama or similar LLMs LangChain, LangGraph, Semantic Kernel, CrewAI, AutoGen or equivalent frameworks RAG, vector databases and embeddings Azure AI, AWS AI or Google Vertex AI MLOps, CI/CD and cloud-native deployment Docker, Kubernetes and modern software engineering practices What ...

covers the full AI/ML engineering lifecycle, from discovery to deployment and monitoring. Responsibilities include Designing and implementing agentic systems using techniques spanning RAG, grounding, prompt engineering, and orchestration on a GCP‐first stack. Building and maintaining production ML pipelines and services for non‐GenAI use cases (e.g. recommender … Terraform), experiment tracking, model registry, and monitoring. Proven experience deploying and operating ML systems in production (batch and real‐time). Familiarity with RAG architectures, prompt engineering, guardrails and evaluation techniques. Previous experience developing agentic capabilities, such as agent skills, MCP servers, tool usage. Strong grasp of security, privacy ...

agent orchestration, tool use, skills use, and memory systems — and work hands‐on with foundation models through fine‐tuning, retrieval‐augmented generation (RAG), and custom model integration. A part of your work will also involve engineering the AI context layer that makes these systems … faithfulness, translating findings into design improvements Architect and implement foundation model integrations — selecting the right models, invocation patterns, and customization approaches (fine‐tuning, RAG, custom integration) based on capability, cost, and performance trade‐offs Design and build model adaptation and fine‐tuning pipelines, applying working knowledge of transformer‐based architectures ...

Studio. Experience designing and building LLM agents or AI-powered workflows using Azure OpenAI or similar technologies Knowledge of Retrieval Augmented Generation (RAG), vector search or agent orchestration frameworks would be advantageous If this sounds like a good fit, apply now as interviews commence ...

Linux-based environments and proficient in 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 ...

shape strategy and drive delivery within a large, complex organisation Knowledge of modern AI approaches, including areas such as Retrieval Augmented Generation (RAG), prompt engineering, observability and evaluation Experience in cyber security, fraud analytics, behavioural analytics or threat detection would be particularly valuable This ...

shape strategy and drive delivery within a large, complex organisation Knowledge of modern AI approaches, including areas such as Retrieval Augmented Generation (RAG), prompt engineering, observability and evaluation Experience in cyber security, fraud analytics, behavioural analytics or threat detection would be particularly valuable This ...

shape strategy and drive delivery within a large, complex organisation Knowledge of modern AI approaches, including areas such as Retrieval Augmented Generation (RAG), prompt engineering, observability and evaluation Experience in cyber security, fraud analytics, behavioural analytics or threat detection would be particularly valuable. This ...

mapping tools. Familiarity with Microsoft 365 cloud ecosystem, Azure integrations, document management systems and virtual data rooms. Exposure to generative AI integration, prompt engineering, RAG architecture and LLM orchestration frameworks. Understanding of security architecture principles and legal‐sector information governance. Legal & Commercial Skills Proven experience in a law firm, ALSP ...

work is genuinely varied: one week you’re designing a data API, the next you’re improving retrieval quality in a RAG pipeline, the next you’re working with infrastructure to get a service into production. We’re looking for someone who finds that energising rather than uncomfortable. ...

egress controls). Strong understanding of AI/LLM capabilities and risks across the lifecycle (model onboarding/ingestion, retrieval/RAG patterns, model serving) and associated control points (traceability, access, data handling), including assessing control design and operational effectiveness in fast‐changing environments. Experience with agentic ...