401 to 425 of 960 Retrieval-Augmented Generation Jobs in England

model evaluation, testing, validation, and responsible AI. Design and improve AI systems using techniques such as prompt engineering, retrieval augmented generation (RAG), and AI agents. Mentor data scientists and provide technical leadership through code reviews and coaching. Partner with engineering teams to deliver scalable … What we're looking for Extensive experience developing AI and machine learning solutions in production environments. Strong expertise in large language models, generative AI, RAG, prompt engineering, and agentic AI. Excellent Python programming skills and experience with modern AI and data science frameworks. Strong foundation in statistics, machine learning ...

enterprise standards for: Domain-aligned AI capabilities and reusable AI services AI lifecycle management frameworks (MLOps, LLMOps, AgentOps) AI-aligned data patterns (feature stores, RAG pipelines, inference architectures) Review and guide solution designs to ensure they are secure, scalable, resilient, and cost-effective. Collaboration & Enterprise Alignment Work closely with domain … data product and AI operating model. Knowledge, Experience & Capabilities Deep knowledge of modern AI architectures on AWS, including Generative AI, RAG (Retrieval-Augmented Generation), and large-scale asynchronous inference workloads. Ability to translate enterprise business problems into AI-driven Products, promoting decentralized model ownership ...

methodologies and AI-native IDEs, covering positioning, workshop delivery, and customer engagement across the full lifecycleCreate best practices and architectural guidance on Next-Generation Software Development, being a thought leader on the area. Be the technical reference on Next-Gen Development for the EMEA Partner Organization, collecting … microservices, or language/framework upgrades- Knowledge of generative AI foundations: large language models, prompt engineering, context engineering, retrieval augmented generation (RAG)- Experience enabling or developing partner ecosystems (system integrators, ISVs, consulting firms)- Familiarity with IDE extensibility, developer tooling, and software supply chain practices ...

native IDEs, covering positioning, workshop delivery, and customer engagement across the full lifecycle Create best practices and architectural guidance on Next-Generation Software Development, being a thought leader on the area. Be the technical reference on Next-Gen Development for the EMEA Partner Organization, collecting and exposing … microservices, or language/framework upgrades Knowledge of generative AI foundations: large language models, prompt engineering, context engineering, retrieval augmented generation (RAG) Experience enabling or developing partner ecosystems (system integrators, ISVs, consulting firms) Familiarity with IDE extensibility, developer tooling, and software supply chain practices ...

equally comfortable applying proven machine-learning techniques to traditional analytics problems and working with the latest generative AI (large language models, retrieval-augmented generation, and agent-based applications). You enjoy building, you write dependable code, and you turn well-defined designs into working … machine learning components within client projects to the standards and designs set by senior colleagues.Develop GenAI and LLM-based features (prompting, retrieval-augmented generation, and simple agentic workflows) alongside more traditional ML models.Deliver classical data science tasks (data preparation, feature engineering, model training ...

develop and implement enterprise AI solutions using technologies including Large Language Models, ChatGPT/OpenAI, Microsoft Copilot, Azure AI, Retrieval Augmented Generation (RAG) and UiPath. You'll also develop AI assistants, copilots and automated workflows, integrating AI into systems including ERP, CRM, PLM, SharePoint … have strong technical experience across Python, OpenAI APIs, Prompt Engineering, Azure OpenAI Services, Microsoft Copilot Studio, UiPath, Power Automate, REST APIs and RAG architectures, alongside experience integrating technology into enterprise systems. You'll also be a strong communicator who can translate complex AI concepts for non-technical audiences, work effectively ...

analysing customer behaviour to identify growth opportunities; developing segmentation, propensity, churn or next-best-action models; building and evaluating generative AI and retrieval-augmented generation solutions; or developing agentic workflows that improve marketing, commerce or customer service processes.You will move between hands-on delivery … machine learning is more appropriate than an LLM.Generative AI and agentic systems. Practical understanding of generative AI architectures and techniques, including retrieval-augmented generation, LLM evaluation, prompt and context engineering, and agentic patterns. You understand their benefits, limitations and trade-offs.Data and production foundations. ...

analysing customer behaviour to identify growth opportunities; developing segmentation, propensity, churn or next-best-action models; building and evaluating generative AI and retrieval-augmented generation solutions; or developing agentic workflows that improve marketing, commerce or customer service processes. You will move between hands … machine learning is more appropriate than an LLM.Generative AI and agentic systems. Practical understanding of generative AI architectures and techniques, including retrieval-augmented generation, LLM evaluation, prompt and context engineering, and agentic patterns. You understand their benefits, limitations and trade-offs. Data and production ...

workflows using frameworks such as LangGraph and related orchestration tools.Apply modern techniques in:NLPGenerative AIEmbeddings and semantic representationsRetrieval-augmented generation (RAG)AI reasoning and workflow orchestrationEvaluate emerging AI models, tools, and frameworks and contribute recommendations for experimentation and adoption.Contribute to prompt engineering, grounding strategies, context management … hallucination mitigation efforts.Support integration of scientific metadata, ontologies, and knowledge assets into AI-powered workflows.Search, Retrieval & RAG SystemsDesign, develop, and optimize search and retrieval pipelines, including lexical, vector, and hybrid retrieval approaches.Contribute to the development and enhancement of RAG systems that integrate LLMs with ...

partnership with cross‐functional teams Preferred Qualifications, Capabilities, and Skills Experience with NLP and generative AI, including large language models, retrieval‐augmented generation, tool and function calling, agentic workflows, multi‐agent orchestration, and related evaluation and safety patterns Familiarity with agentic building blocks ...

data pipelines and platform components Experience of coaching and mentoring data engineers to achieve successful outcomes Familiarity with AI-focused data engineering, including RAG systems, vector databases, embedding pipelines, and semantic indexing A proven record of collaboration with colleagues and stakeholders Process mapping and supporting documentation production Test plan formulation ...

Migration of analytical/data science workloads (convert and migrate R development/Libraries to Databricks). AI/ML, LLM integration, model lifecycle, RAG/vector retrieval or model-serving experience. Large-scale enterprise platform transformation and regulated-industry experience. Strong cost optimisation and FinOps delivery experience ...

platform. This hands-on leadership role focuses on scalable engineering patterns, accelerating delivery, and mentoring development teams. You will design and oversee LLM, RAG, and Agentic AI integrations across Azure, AWS, and GCP, collaborate with architects to ensure secure, maintainable solutions, and set standards for observability, governance, and #J ...

track record delivering enterprise-scale AI/ML solutions into production Strong experience leading technical teams and complex transformation programmes Deep expertise in LLMs, RAG architectures, Prompt Engineering and Generative AI frameworks such as LangChain or LangGraph Hands-on experience with Python, PyTorch, TensorFlow, MLOps/LLMOps and cloud platforms ...

track record delivering enterprise-scale AI/ML solutions into production Strong experience leading technical teams and complex transformation programmes Deep expertise in LLMs, RAG architectures, Prompt Engineering and Generative AI frameworks such as LangChain or LangGraph Hands‐on experience with Python, PyTorch, TensorFlow, MLOps/LLMOps and cloud platforms ...

track record delivering enterprise-scale AI/ML solutions into production Strong experience leading technical teams and complex transformation programmes Deep expertise in LLMs, RAG architectures, Prompt Engineering and Generative AI frameworks such as LangChain or LangGraph Hands-on experience with Python, PyTorch, TensorFlow, MLOps/LLMOps and cloud platforms ...

track record delivering enterprise-scale AI/ML solutions into production Strong experience leading technical teams and complex transformation programmes Deep expertise in LLMs, RAG architectures, Prompt Engineering and Generative AI frameworks such as LangChain or LangGraph Hands-on experience with Python, PyTorch, TensorFlow, MLOps/LLMOps and cloud platforms ...

willingness to work with or learn GoHands-on experience building and operating production AI applications using large language models and agentic frameworksUnderstanding of RAG, MCP, LangGraph or similar technologies, including tool integration and prompt designExperience creating reliable AI agents through evaluation, guardrails and token and cost optimisationProficiency with Docker, Kubernetes ...

work with or learn Go Hands-on experience building and operating production AI applications using large language models and agentic frameworks Understanding of RAG, MCP, LangGraph or similar technologies, including tool integration and prompt design Experience creating reliable AI agents through evaluation, guardrails and token and cost optimisation Proficiency with ...

integrating Generative AI/LLM functionality directly into software products Working with technologies such as OpenAI, Azure OpenAI, Claude, Gemini or local models Exploring RAG, AI agents, Semantic Kernel, MCP, vector search and intelligent workflows Engineering around the realities of production AI: accuracy, security, validation, guardrails, latency and cost Working ...

integrating Generative AI/LLM functionality directly into software products Working with technologies such as OpenAI, Azure OpenAI, Claude, Gemini or local models Exploring RAG, AI agents, Semantic Kernel, MCP, vector search and intelligent workflows Engineering around the realities of production AI: accuracy, security, validation, guardrails, latency and cost Working ...

integrating Generative AI/LLM functionality directly into software products Working with technologies such as OpenAI, Azure OpenAI, Claude, Gemini or local models Exploring RAG, AI agents, Semantic Kernel, MCP, vector search and intelligent workflows Engineering around the realities of production AI: accuracy, security, validation, guardrails, latency and cost Working ...

ExperienceSolution Architecture, Enterprise Architecture or AI Architecture experience.Strong understanding of Generative AI, Large Language Models (LLMs) and AI agent frameworks.Experience designing AI solutions using RAG, prompt engineering and knowledge-grounded architectures.Expertise in Microsoft AI technologies, including Microsoft 365 Copilot, Copilot Studio, Azure AI and/or Power Platform.Experience delivering solutions ...

Enterprise Architecture or AI Architecture experience. Strong understanding of Generative AI, Large Language Models (LLMs) and AI agent frameworks. Experience designing AI solutions using RAG, prompt engineering and knowledge-grounded architectures. Expertise in Microsoft AI technologies, including Microsoft 365 Copilot, Copilot Studio, Azure AI and/or Power Platform. Experience ...

Python and JavaScript Hands-on experience with backend frameworks and modern frontend frameworks Deep knowledge of Generative AI and agent-based AI frameworks including RAG and orchestration patterns Strong experience working with vector databases and AI-specific data stores Solid understanding of AI and ML models, LLMs and generative ...