551 to 575 of 886 Retrieval-Augmented Generation Jobs in England

develop new skills and hone existing ones. We work for a huge variety of interesting, international, and world-leading clients on exciting next generation technology-enabled projects. We are looking for candidates with AI/GenAI Architect based expertise to join us, working in fast-paced teams with … content around data design, architecture and engineering like collateral and playbooks on KX, improving our artefacts and strategies.Knowledge of generative AI architectural patterns including RAG & fine tuning.Experience training & deploying machine learning models using a range of techniques (e.g. Classification, Regression, Neural Networks, etc).Experience with developing and deploying applications ...

read-only pulls and progressing to bidirectional integration.**AI & Agentic Workflows*** Design, deploy and orchestrate agentic AI workflows using frameworks such as LangGraph; implement RAG pipelines, fine-tuned models and vector database integrations within the assigned business domain.* Operate the end-to-end delivery toolchain (AWS, GitLab, Docker, CI/… pipelines, REST/gRPC APIs and microservices architecture; identity and access management with OIDC/SAML and Azure Entra ID.* Experience with LLMs, RAG systems, prompt engineering and AI evaluation frameworks; familiarity with MLOps, model deployment and AI observability/guardrails; working use of AI-assisted development tools (e.g. Claude ...

based development when needed, particularly during critical delivery phases or proof‐of‐concept work. Support the design and delivery of Generative AI solutions, including RAG architectures, prompt engineering, and integration with Azure AI services (e.g., Azure OpenAI, Azure AI Search). Ensure robust MLOps practices are followed, including model versioning … experiment tracking and model management, and Spark-based data processing. Familiarity with Generative AI concepts and tooling, including working with LLMs, prompt engineering, RAG patterns, and vector search. A solid understanding of MLOps principles, including CI/CD for models, automated testing, and monitoring of deployed solutions. Cloud platform experience ...

will play a key role in shaping how AI, agents, data, and ontology-driven business context become foundational capabilities across the next generation of Infor Manufacturing solutions.A Typical Day in the Life Includes:Defining the AI architecture, standards, and technical strategy for MES and the Manufacturing portfolio. Designing … practices and technologies. Proven experience designing and delivering production AI solutions using Large Language Models (LLMs). Experience with Retrieval Augmented Generation (RAG), agentic architectures, AI orchestration frameworks, and tool-based AI systems. Experience integrating AI capabilities into enterprise software products. Experience designing APIs ...

will play a key role in shaping how AI, agents, data, and ontology-driven business context become foundational capabilities across the next generation of Infor Manufacturing solutions. A Typical Day in the Life Includes: Defining the AI architecture, standards, and technical strategy for MES and the Manufacturing portfolio. … practices and technologies. Proven experience designing and delivering production AI solutions using Large Language Models (LLMs). Experience with Retrieval Augmented Generation (RAG), agentic architectures, AI orchestration frameworks, and tool-based AI systems. Experience integrating AI capabilities into enterprise software products. Experience designing APIs ...

rather than hype to determine whether an AI approach is actually working. It would be advantageous if you have experience with: RAG (Retrieval-Augmented Generation) Agentic workflows and tool use Fine-tuning Vector search and embeddings Retrieval pipelines LLM orchestration frameworks such ...

rather than hype to determine whether an AI approach is actually working. It would be advantageous if you have experience with: RAG (Retrieval-Augmented Generation) Agentic workflows and tool use Fine-tuning Vector search and embeddings Retrieval pipelines LLM orchestration frameworks such ...

rather than hype to determine whether an AI approach is actually working. It would be advantageous if you have experience with: RAG (Retrieval-Augmented Generation) Agentic workflows and tool use Fine-tuning Vector search and embeddings Retrieval pipelines LLM orchestration frameworks such ...

services with existing enterprise applications including Microsoft 365, Dynamics and other University systems. Building secure AI solutions using Retrieval Augmented Generation (RAG), prompt engineering and orchestration techniques. Develop Python-based services, APIs and automation scripts to support AI products. Use Power BI to develop ...

e.g., Google Cloud Platform (GCP)). Experience building pipelines for structured and unstructured data using both vector databases and retrieval augmented generation (RAG) like architectures to power enterprise AI solutions. Experience leading technical discovery sessions with customers. Active, or the ability to obtain ...

e.g., Google Cloud Platform (GCP)). Experience building pipelines for structured and unstructured data using both vector databases and retrieval augmented generation (RAG) like architectures to power enterprise AI solutions. Experience leading technical discovery sessions with customers. Active, or the ability to obtain ...

e.g., Google Cloud Platform (GCP)). Experience building pipelines for structured and unstructured data using both vector databases and retrieval augmented generation (RAG) like architectures to power enterprise AI solutions. Experience leading technical discovery sessions with customers. Active, or the ability to obtain ...

meaningful way, whether for security testing, security research, or your own workflows* Enough understanding of how LLMs work (context windows, tool use, RAG, agentic chaining) to reason about where they can go wrong* Familiarity with AI testing tools or frameworks, even from personal research or experimentation, is a real plus ...

tools in a meaningful way, whether for security testing, security research, or your own workflowsEnough understanding of how LLMs work (context windows, tool use, RAG, agentic chaining) to reason about where they can go wrongFamiliarity with AI testing tools or frameworks, even from personal research or experimentation, is a real ...

/AI, guiding customers and the Field Engineering team to design production‐grade AI solutions on the Databricks platform. You will drive GenAI initiatives, RAG architectures, agentic systems, AI observability, and NLQ of structured data, while mentoring peers and influencing the platform roadmap. Some travel may be required. #J ...

experience driving cloud/AI transformation within Insurance, Financial Services, or similarly highly regulated industries. Technical Acumen: A strong architectural understanding of GenAI concepts (RAG, AI Agents, Agentic Workflows) and DevSecOps automation. Delivery Mastery: Expertise in benefits management, project planning, and crisis mitigation for large-scale enterprise deployments. To Apply ...

experience driving cloud/AI transformation within Insurance, Financial Services, or similarly highly regulated industries. Technical Acumen: A strong architectural understanding of GenAI concepts (RAG, AI Agents, Agentic Workflows) and DevSecOps automation. Delivery Mastery: Expertise in benefits management, project planning, and crisis mitigation for large-scale enterprise deployments. To Apply ...

experience driving cloud/AI transformation within Insurance, Financial Services, or similarly highly regulated industries. Technical Acumen: A strong architectural understanding of GenAI concepts (RAG, AI Agents, Agentic Workflows) and DevSecOps automation. Delivery Mastery: Expertise in benefits management, project planning, and crisis mitigation for large-scale enterprise deployments. To Apply ...

experience with software development using Python or similar coding languages. Experience building pipelines for structured and unstructured data using both vector databases and RAG-like architectures to power enterprise AI solutions. Experience taking production-grade AI-driven solutions from conception to launch, and architecting AI systems on cloud platforms (e.g. ...

experience with software development using Python or similar coding languages. Experience building pipelines for structured and unstructured data using both vector databases and RAG-like architectures to power enterprise AI solutions. Experience taking production-grade AI-driven solutions from conception to launch, and architecting AI systems on cloud platforms (e.g. ...

skills with Python, JavaScript/Node, TypeScript, or similar languages.Strong SEO/GEO/content delivery systems experienceExperience with LLM‐based applications, AI agents, RAG systems, or workflow automation.Ability to interpret ABV insights and translate them into actionable optimizations.Excellent communication and customer‐facing skills.Preferred: Experience with AEM, Adobe Experience Platform ...

latency. Technical Must-Haves Expert-level Python with a track record of shipping production LLM systems Hands-on experience designing LLM agents and RAG pipelines. Proficiency with AI evaluation frameworks and end-to-end evaluation pipelines. Solid grounding in NLP fundamentals (tokenisation, embeddings, bias handling). Ability to juggle token ...

productive faster. Bonus points Previously founded a company. Startup experience. Design tooling literacy (Figma), or a design background. Experience with LLM-backed product features: RAG, embeddings, evaluation. Go, or a willingness to learn it. It's what most of our backend is written in. Data or analytics engineering experience (Python ...

equivalent experience Technical Skill Set Data Platforms: Cloud DWH/DL (GCP, Snowflake, Databricks, AWS, Azure), ingestion pipelines, data modelling, governance AI & Agentic: GenAI, RAG, vector stores, agent lifecycle, MCP/A2A interoperability Salesforce Platform: Data 360, Agentforce, Agent Builder - deep architectural fluency Integration/BI: MuleSoft, hyperscaler SDKs, Tableau ...

plusDegree or equivalent experienceTechnical Skill SetData Platforms: Cloud DWH/DL (GCP, Snowflake, Databricks, AWS, Azure), ingestion pipelines, data modelling, governanceAI & Agentic: GenAI, RAG, vector stores, agent lifecycle, MCP/A2A interoperabilitySalesforce Platform: Data 360, Agentforce, Agent Builder — deep architectural fluencyIntegration/BI: MuleSoft, hyperscaler SDKs, Tableau/PowerBI/ ...